From 891d57b16d954fa665ac6266290fe93fe6d66502 Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 10:48:52 -0500
Subject: [PATCH 01/28] Update README.md
---
README.md | 15 ++++++++++-----
1 file changed, 10 insertions(+), 5 deletions(-)
diff --git a/README.md b/README.md
index 9842d7d..b715aee 100644
--- a/README.md
+++ b/README.md
@@ -20,15 +20,20 @@ All these factors make idenfitfying factual and unbiased information regarding n
# Our Solution
-Our primary aim is to create an interactive visualization dashboard of 1000+ raw and minimally processed foods and their nutritional contents (sourced from the United States Department (USDA) of Agriculture Food Data Central resource). You can reach our site XXXXXXXXX and experiment with 1) view nutrition content for a single food, 2) compare multiple food items’ nutritional content, and 3) view various food combinations and their resulting nutrition content to determine whether or not their diet satisfies recommended nutritional needs (based on USDA Dietary Reference Intakes (DRI)).
+Our primary aim for this project is to create an interactive visualization dashboard of a selection of foods and their nutritional contents (sourced from the United States Department of Agriculture (USDA) Food Data Central resource).
-# description of our project
+# Visualization platform
-We're developing a web app that enables individuals to learn about the nutritional content of the foods they eat. Both macronutrient and micronutrient data on [hundreds?] of food items are immediately available upon a simple choice in a drop-down menu of food items.
+You can reach our Streamlit dashboard here:https://share.streamlit.io/tantar/uncovering-the-nutritional-landscape-of-food/main/UNLF.py and experiment with Individual, Comparison, and Diet views.
-Our web app enables users to compare different food items and their nutritional value, as well as provide data on whether or not selected foods meet daily recommended nutritional guidelines set forth by the USDA.
+Individual view: If a user was interested in viewing the nutrition content for a single food item, they can select the Individual Food option. Within this option, a food such as ocean perch can be evaluated for its carbohydrate, protein, and fiber content in comparison to USDA DRIs as well as a selection of nutrients including: Vitamins A, D, E, K, and C, B vitamins, calcium, copper, iron, magnesium, phosphorus, potassium, selenium, sodium, zinc, choline, and total water. An example of this visualization is shown below.
+
+Comparison view: For users interested in viewing a nutrient comparison between multiple foods, the Diet view allows for selection of various foods of interest and reports nutrient content. All nutrient options are consistent with those available in the Individual view. This view is specifically color-coded to allow for consistent identification of what food item is contributing what nutrient content. This visualization can be seen here.
+
+Diet + Recommendation view: This view is for individuals interested in eliciting feedback regarding suggested foods to consume given a current dietary intake. Within the Diet with Recommendations view users can select multiple foods and will receive the resulting nutrition content of each food. Additionally, in this view users will receive three recommended foods that are specifically selected to improve the nutrient content of the listed diet to meet dietary reference ranges.
+
+All data on Dietary Reference Intakes are from the USDA (https://www.nal.usda.gov/sites/default/files/fnic_uploads/recommended_intakes_individuals.pdf) and are currently only applicable for individuals ages 19-30 years old.
-# link to our Streamlit site
# information for streamlit user
- include information about what the inputs are and what the outputs are (figure/ workflow diagram), describe them distinctly
From 09148a888b61c4ae4751b4e9e817e2d99f4edf65 Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 10:50:19 -0500
Subject: [PATCH 02/28] Update README.md
---
README.md | 9 ++++-----
1 file changed, 4 insertions(+), 5 deletions(-)
diff --git a/README.md b/README.md
index b715aee..31e46cb 100644
--- a/README.md
+++ b/README.md
@@ -22,7 +22,7 @@ All these factors make idenfitfying factual and unbiased information regarding n
Our primary aim for this project is to create an interactive visualization dashboard of a selection of foods and their nutritional contents (sourced from the United States Department of Agriculture (USDA) Food Data Central resource).
-# Visualization platform
+# Visualization Dashboard
You can reach our Streamlit dashboard here:https://share.streamlit.io/tantar/uncovering-the-nutritional-landscape-of-food/main/UNLF.py and experiment with Individual, Comparison, and Diet views.
@@ -42,11 +42,10 @@ All data on Dietary Reference Intakes are from the USDA (https://www.nal.usda.go
# information for those looking to replicate
- instructions for what to install, any dependencies, any example code we may be able to include
-# planned features/ what's next
-We hope to continue refining our dashboard to include greater functionality and customization for users in a future codeathon. Our next steps for this project are to 1) increase the number of foods and nutrients our dashboard can reference, 2) automate file ingestion, 3) include all age bracket options for dietary reference intakes, and 4) pursue user testing and elicit feedback.
-
-# datasets used
+# Future Directions
+We hope to continue refining our dashboard to include greater functionality and customization for users in a future codeathon. Our next steps for this project are to 1) increase the number of foods and nutrients our dashboard can reference, 2) automate updating of data from USDA FDC 3) include all age bracket options for dietary reference intakes, and 4) pursue user testing and elicit feedback.
+# Datasets Used for this Project
- "Uncovering the Nutritional Landscape of Food by Kim" et al. [S1 Dataset. Foods analyzed in this study](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0118697#references)
- [USDA FoodData Central](https://fdc.nal.usda.gov/download-datasets.html) [April 2019 (CSV – 6.1MB)](https://fdc.nal.usda.gov/fdc-datasets/FoodData_Central_sr_legacy_food_csv_%202019-04-02.zip)
From 8bcee7289bded8596e4c5bd66a740e27c76be89a Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 11:00:29 -0500
Subject: [PATCH 03/28] Update README.md
---
README.md | 9 ++++-----
1 file changed, 4 insertions(+), 5 deletions(-)
diff --git a/README.md b/README.md
index 31e46cb..7e71b69 100644
--- a/README.md
+++ b/README.md
@@ -35,12 +35,11 @@ Diet + Recommendation view: This view is for individuals interested in eliciting
All data on Dietary Reference Intakes are from the USDA (https://www.nal.usda.gov/sites/default/files/fnic_uploads/recommended_intakes_individuals.pdf) and are currently only applicable for individuals ages 19-30 years old.
-# information for streamlit user
-- include information about what the inputs are and what the outputs are (figure/ workflow diagram), describe them distinctly
-- use some of the screenshot pieces here if possible from our use case
+# For users of our Streamlit
+This freely available dashboard only requires internet access. Any individual who is interested in using the dashboard is able to interact with it on their local machine.
-# information for those looking to replicate
-- instructions for what to install, any dependencies, any example code we may be able to include
+# For those looking to replicate our Streamlit
+Streamlit is a python based platform. Individuals looking to replicate and edit the dashboard created for this project will need to download python in order to do so. If interested in using our code, that is made readily available within our GitHub and can also be found in a condensed file on Zenodo. LINK
# Future Directions
We hope to continue refining our dashboard to include greater functionality and customization for users in a future codeathon. Our next steps for this project are to 1) increase the number of foods and nutrients our dashboard can reference, 2) automate updating of data from USDA FDC 3) include all age bracket options for dietary reference intakes, and 4) pursue user testing and elicit feedback.
From 0b4f70114ae07d1e6e9d5c5fdfb6a604a44c5fcc Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 11:01:13 -0500
Subject: [PATCH 04/28] Update README.md
---
README.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/README.md b/README.md
index 7e71b69..cbb398c 100644
--- a/README.md
+++ b/README.md
@@ -42,7 +42,7 @@ This freely available dashboard only requires internet access. Any individual wh
Streamlit is a python based platform. Individuals looking to replicate and edit the dashboard created for this project will need to download python in order to do so. If interested in using our code, that is made readily available within our GitHub and can also be found in a condensed file on Zenodo. LINK
# Future Directions
-We hope to continue refining our dashboard to include greater functionality and customization for users in a future codeathon. Our next steps for this project are to 1) increase the number of foods and nutrients our dashboard can reference, 2) automate updating of data from USDA FDC 3) include all age bracket options for dietary reference intakes, and 4) pursue user testing and elicit feedback.
+We hope to continue refining our dashboard to include greater functionality and customization for users in a future codeathon. Our next steps for this project are to 1) increase the number of foods and nutrients our dashboard can reference, 2) automate updating of data from USDA FDC 3) include all age bracket options for dietary reference intakes, 4) allow for the serving size to be customized, and 5) pursue user testing and elicit feedback.
# Datasets Used for this Project
- "Uncovering the Nutritional Landscape of Food by Kim" et al. [S1 Dataset. Foods analyzed in this study](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0118697#references)
From 19c2bd5f5543f5441d820859bd918352609b4941 Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 11:05:53 -0500
Subject: [PATCH 05/28] Update README.md
---
README.md | 8 ++++++--
1 file changed, 6 insertions(+), 2 deletions(-)
diff --git a/README.md b/README.md
index cbb398c..5eb8e1c 100644
--- a/README.md
+++ b/README.md
@@ -28,9 +28,13 @@ You can reach our Streamlit dashboard here:https://share.streamlit.io/tantar/unc
Individual view: If a user was interested in viewing the nutrition content for a single food item, they can select the Individual Food option. Within this option, a food such as ocean perch can be evaluated for its carbohydrate, protein, and fiber content in comparison to USDA DRIs as well as a selection of nutrients including: Vitamins A, D, E, K, and C, B vitamins, calcium, copper, iron, magnesium, phosphorus, potassium, selenium, sodium, zinc, choline, and total water. An example of this visualization is shown below.
+
Comparison view: For users interested in viewing a nutrient comparison between multiple foods, the Diet view allows for selection of various foods of interest and reports nutrient content. All nutrient options are consistent with those available in the Individual view. This view is specifically color-coded to allow for consistent identification of what food item is contributing what nutrient content. This visualization can be seen here.
-Diet + Recommendation view: This view is for individuals interested in eliciting feedback regarding suggested foods to consume given a current dietary intake. Within the Diet with Recommendations view users can select multiple foods and will receive the resulting nutrition content of each food. Additionally, in this view users will receive three recommended foods that are specifically selected to improve the nutrient content of the listed diet to meet dietary reference ranges.
+
+Diet + Recommendation view: This view is for individuals interested in eliciting feedback regarding suggested foods to consume given a current dietary intake. Within the Diet with Recommendations view users can select multiple foods and their nutrients of interest to receive visualization of that data. Additionally, in this view users will receive three recommended foods that are specifically selected to improve the nutrient content of the listed diet to meet dietary reference ranges. Dietary limitation and activity level information is not currently functional within this view.An example of this visualization is displayed below.
+
+
All data on Dietary Reference Intakes are from the USDA (https://www.nal.usda.gov/sites/default/files/fnic_uploads/recommended_intakes_individuals.pdf) and are currently only applicable for individuals ages 19-30 years old.
@@ -42,7 +46,7 @@ This freely available dashboard only requires internet access. Any individual wh
Streamlit is a python based platform. Individuals looking to replicate and edit the dashboard created for this project will need to download python in order to do so. If interested in using our code, that is made readily available within our GitHub and can also be found in a condensed file on Zenodo. LINK
# Future Directions
-We hope to continue refining our dashboard to include greater functionality and customization for users in a future codeathon. Our next steps for this project are to 1) increase the number of foods and nutrients our dashboard can reference, 2) automate updating of data from USDA FDC 3) include all age bracket options for dietary reference intakes, 4) allow for the serving size to be customized, and 5) pursue user testing and elicit feedback.
+We hope to continue refining our dashboard to include greater functionality and customization for users in a future codeathon. Our next steps for this project are to 1) increase the number of foods and nutrients our dashboard can reference, 2) automate updating of data from USDA FDC 3) include all age bracket options for dietary reference intakes, 4) include activity level and dietary limitation specific customizations 5) allow for the serving size to be customized, and 6) pursue user testing and elicit feedback.
# Datasets Used for this Project
- "Uncovering the Nutritional Landscape of Food by Kim" et al. [S1 Dataset. Foods analyzed in this study](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0118697#references)
From 283c6a1c45affdeb50258c9ad9fb5b77939090ef Mon Sep 17 00:00:00 2001
From: tantar <69642120+tantar@users.noreply.github.com>
Date: Thu, 12 Aug 2021 12:26:21 -0400
Subject: [PATCH 06/28] Update README.md
---
README.md | 15 ++++++---------
1 file changed, 6 insertions(+), 9 deletions(-)
diff --git a/README.md b/README.md
index 5eb8e1c..0737224 100644
--- a/README.md
+++ b/README.md
@@ -24,16 +24,13 @@ Our primary aim for this project is to create an interactive visualization dashb
# Visualization Dashboard
-You can reach our Streamlit dashboard here:https://share.streamlit.io/tantar/uncovering-the-nutritional-landscape-of-food/main/UNLF.py and experiment with Individual, Comparison, and Diet views.
+You can reach our Streamlit dashboard here:https://share.streamlit.io/tantar/uncovering-the-nutritional-landscape-of-food/main/UNLF.py. Currently we support three different types of visualizations for individual foods, comparison between foods, and the user's personal diet with recommendations.
-Individual view: If a user was interested in viewing the nutrition content for a single food item, they can select the Individual Food option. Within this option, a food such as ocean perch can be evaluated for its carbohydrate, protein, and fiber content in comparison to USDA DRIs as well as a selection of nutrients including: Vitamins A, D, E, K, and C, B vitamins, calcium, copper, iron, magnesium, phosphorus, potassium, selenium, sodium, zinc, choline, and total water. An example of this visualization is shown below.
+Individual view: If a user was interested in viewing the nutrition content for a single food item, they can select the Individual Food option. Within this option, a food such as ocean perch can be evaluated for its carbohydrate, protein, and fiber content in comparison to USDA daily recommended intake, as well as a selection of nutrients including: Vitamins A, D, E, K, and C, B vitamins, calcium, copper, iron, magnesium, phosphorus, potassium, selenium, sodium, and zinc. An example of this visualization is shown below.
+Comparison view: For users interested in viewing a nutrient comparison between multiple foods, the Comparison view allows for selection of various foods of interest and reports nutrient content. All nutrient options are consistent with those available in the Individual view, however this view is specifically color-coded to allow for consistent identification of what food item is contributing to each nutrient's daily recommended intake. This visualization can be seen here.
-Comparison view: For users interested in viewing a nutrient comparison between multiple foods, the Diet view allows for selection of various foods of interest and reports nutrient content. All nutrient options are consistent with those available in the Individual view. This view is specifically color-coded to allow for consistent identification of what food item is contributing what nutrient content. This visualization can be seen here.
-
-
-Diet + Recommendation view: This view is for individuals interested in eliciting feedback regarding suggested foods to consume given a current dietary intake. Within the Diet with Recommendations view users can select multiple foods and their nutrients of interest to receive visualization of that data. Additionally, in this view users will receive three recommended foods that are specifically selected to improve the nutrient content of the listed diet to meet dietary reference ranges. Dietary limitation and activity level information is not currently functional within this view.An example of this visualization is displayed below.
-
+Diet with Recommendations view: This view is for individuals interested in gaining insight into how their current diet meets the daily recommended intake for each nutrient with recommendations on how to meet their daily needs. Within the Diet with Recommendations view users can select multiple foods and their nutrients of interest to receive visualization of that data. Additionally, in this view users will receive three recommended foods that are specifically selected to improve the nutrient content of the listed diet to meet dietary reference ranges. Dietary limitation and activity level information is not currently functional within this view.An example of this visualization is displayed below.
All data on Dietary Reference Intakes are from the USDA (https://www.nal.usda.gov/sites/default/files/fnic_uploads/recommended_intakes_individuals.pdf) and are currently only applicable for individuals ages 19-30 years old.
@@ -43,7 +40,7 @@ All data on Dietary Reference Intakes are from the USDA (https://www.nal.usda.go
This freely available dashboard only requires internet access. Any individual who is interested in using the dashboard is able to interact with it on their local machine.
# For those looking to replicate our Streamlit
-Streamlit is a python based platform. Individuals looking to replicate and edit the dashboard created for this project will need to download python in order to do so. If interested in using our code, that is made readily available within our GitHub and can also be found in a condensed file on Zenodo. LINK
+First, an individual would need to download the datasets described in the "Datasets Used for this Project" section below. Once the foods and nutrient values are integrated into a single dataset, they would then need to calculate what percent of each nutrients recommended daily intakes it met by individual foods. Individuals looking to replicate and edit the dashboard created for this project will need to download python and install the streamlit and plotly libraries. If interested in using our code, that is made readily available within our GitHub and can also be found in a condensed file on Zenodo. LINK
# Future Directions
We hope to continue refining our dashboard to include greater functionality and customization for users in a future codeathon. Our next steps for this project are to 1) increase the number of foods and nutrients our dashboard can reference, 2) automate updating of data from USDA FDC 3) include all age bracket options for dietary reference intakes, 4) include activity level and dietary limitation specific customizations 5) allow for the serving size to be customized, and 6) pursue user testing and elicit feedback.
@@ -62,7 +59,7 @@ Kyle Pu
Lauren Chan - PhD Candidate in Nutrition at Oregon State University
-Tarek Antar
+Tarek Antar - Postbaccalaurate IRTA in the NIA
Adam Thomas
From b085437fe12b792fc958b6e049883c6e5d0e1977 Mon Sep 17 00:00:00 2001
From: tantar <69642120+tantar@users.noreply.github.com>
Date: Thu, 12 Aug 2021 12:28:08 -0400
Subject: [PATCH 07/28] Update README.md
---
README.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/README.md b/README.md
index 0737224..42abc44 100644
--- a/README.md
+++ b/README.md
@@ -40,7 +40,7 @@ All data on Dietary Reference Intakes are from the USDA (https://www.nal.usda.go
This freely available dashboard only requires internet access. Any individual who is interested in using the dashboard is able to interact with it on their local machine.
# For those looking to replicate our Streamlit
-First, an individual would need to download the datasets described in the "Datasets Used for this Project" section below. Once the foods and nutrient values are integrated into a single dataset, they would then need to calculate what percent of each nutrients recommended daily intakes it met by individual foods. Individuals looking to replicate and edit the dashboard created for this project will need to download python and install the streamlit and plotly libraries. If interested in using our code, that is made readily available within our GitHub and can also be found in a condensed file on Zenodo. LINK
+First, an individual would need to download the datasets described in the "Datasets Used for this Project" section below. Once the foods and nutrient values are integrated into a single dataset, they would then need to calculate what percent of each nutrients recommended daily intakes it met by individual foods. If you are interested in skipping and using our aggregated dataset, it is made available in the data folder of our github. Individuals looking to replicate and edit the dashboard created for this project will need to download python and install the streamlit and plotly libraries. If interested in using our code, that is made readily available within our GitHub and can also be found in a condensed file on Zenodo. LINK
# Future Directions
We hope to continue refining our dashboard to include greater functionality and customization for users in a future codeathon. Our next steps for this project are to 1) increase the number of foods and nutrients our dashboard can reference, 2) automate updating of data from USDA FDC 3) include all age bracket options for dietary reference intakes, 4) include activity level and dietary limitation specific customizations 5) allow for the serving size to be customized, and 6) pursue user testing and elicit feedback.
From a7198d05aa1a4b0306e1d00fb254cd632d1f747a Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 11:30:16 -0500
Subject: [PATCH 08/28] Update README.md
---
README.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/README.md b/README.md
index 42abc44..ffc824f 100644
--- a/README.md
+++ b/README.md
@@ -43,7 +43,7 @@ This freely available dashboard only requires internet access. Any individual wh
First, an individual would need to download the datasets described in the "Datasets Used for this Project" section below. Once the foods and nutrient values are integrated into a single dataset, they would then need to calculate what percent of each nutrients recommended daily intakes it met by individual foods. If you are interested in skipping and using our aggregated dataset, it is made available in the data folder of our github. Individuals looking to replicate and edit the dashboard created for this project will need to download python and install the streamlit and plotly libraries. If interested in using our code, that is made readily available within our GitHub and can also be found in a condensed file on Zenodo. LINK
# Future Directions
-We hope to continue refining our dashboard to include greater functionality and customization for users in a future codeathon. Our next steps for this project are to 1) increase the number of foods and nutrients our dashboard can reference, 2) automate updating of data from USDA FDC 3) include all age bracket options for dietary reference intakes, 4) include activity level and dietary limitation specific customizations 5) allow for the serving size to be customized, and 6) pursue user testing and elicit feedback.
+We hope to continue refining our dashboard to include greater functionality and customization for users in a future codeathon. Our next steps for this project are to 1) increase the number of foods and nutrients our dashboard can reference, 2) automate updating of data from USDA FDC, 3) include macronutrients within the Diet + Recommendation view, 4) include all age bracket options for dietary reference intakes, 5) include activity level and dietary limitation specific customizations 6) allow for the serving size to be customized, and 7) pursue user testing and elicit feedback.
# Datasets Used for this Project
- "Uncovering the Nutritional Landscape of Food by Kim" et al. [S1 Dataset. Foods analyzed in this study](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0118697#references)
From b2da6976273f02a3994da8e4a6bf136a75bbda3d Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 11:33:37 -0500
Subject: [PATCH 09/28] Update README.md
---
README.md | 1 +
1 file changed, 1 insertion(+)
diff --git a/README.md b/README.md
index ffc824f..76e81bf 100644
--- a/README.md
+++ b/README.md
@@ -27,6 +27,7 @@ Our primary aim for this project is to create an interactive visualization dashb
You can reach our Streamlit dashboard here:https://share.streamlit.io/tantar/uncovering-the-nutritional-landscape-of-food/main/UNLF.py. Currently we support three different types of visualizations for individual foods, comparison between foods, and the user's personal diet with recommendations.
Individual view: If a user was interested in viewing the nutrition content for a single food item, they can select the Individual Food option. Within this option, a food such as ocean perch can be evaluated for its carbohydrate, protein, and fiber content in comparison to USDA daily recommended intake, as well as a selection of nutrients including: Vitamins A, D, E, K, and C, B vitamins, calcium, copper, iron, magnesium, phosphorus, potassium, selenium, sodium, and zinc. An example of this visualization is shown below.
+[Screen-Shot-2021-08-12-at-11-33-11-AM.png](https://postimg.cc/WqZxKTyt)
Comparison view: For users interested in viewing a nutrient comparison between multiple foods, the Comparison view allows for selection of various foods of interest and reports nutrient content. All nutrient options are consistent with those available in the Individual view, however this view is specifically color-coded to allow for consistent identification of what food item is contributing to each nutrient's daily recommended intake. This visualization can be seen here.
From 5db6308bdff3e053efa370622f855f54a817d6e0 Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 11:34:00 -0500
Subject: [PATCH 10/28] Update README.md
---
README.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/README.md b/README.md
index 76e81bf..f45e63f 100644
--- a/README.md
+++ b/README.md
@@ -27,7 +27,7 @@ Our primary aim for this project is to create an interactive visualization dashb
You can reach our Streamlit dashboard here:https://share.streamlit.io/tantar/uncovering-the-nutritional-landscape-of-food/main/UNLF.py. Currently we support three different types of visualizations for individual foods, comparison between foods, and the user's personal diet with recommendations.
Individual view: If a user was interested in viewing the nutrition content for a single food item, they can select the Individual Food option. Within this option, a food such as ocean perch can be evaluated for its carbohydrate, protein, and fiber content in comparison to USDA daily recommended intake, as well as a selection of nutrients including: Vitamins A, D, E, K, and C, B vitamins, calcium, copper, iron, magnesium, phosphorus, potassium, selenium, sodium, and zinc. An example of this visualization is shown below.
-[Screen-Shot-2021-08-12-at-11-33-11-AM.png](https://postimg.cc/WqZxKTyt)
+[](https://postimg.cc/WqZxKTyt)
Comparison view: For users interested in viewing a nutrient comparison between multiple foods, the Comparison view allows for selection of various foods of interest and reports nutrient content. All nutrient options are consistent with those available in the Individual view, however this view is specifically color-coded to allow for consistent identification of what food item is contributing to each nutrient's daily recommended intake. This visualization can be seen here.
From 3ed01eeb2e15f8203d918e7ddcfad863cdccdac7 Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 11:34:44 -0500
Subject: [PATCH 11/28] Update README.md
---
README.md | 1 +
1 file changed, 1 insertion(+)
diff --git a/README.md b/README.md
index f45e63f..df5de9c 100644
--- a/README.md
+++ b/README.md
@@ -30,6 +30,7 @@ Individual view: If a user was interested in viewing the nutrition content for a
[](https://postimg.cc/WqZxKTyt)
Comparison view: For users interested in viewing a nutrient comparison between multiple foods, the Comparison view allows for selection of various foods of interest and reports nutrient content. All nutrient options are consistent with those available in the Individual view, however this view is specifically color-coded to allow for consistent identification of what food item is contributing to each nutrient's daily recommended intake. This visualization can be seen here.
+[](https://postimg.cc/nMm5nVdh)
Diet with Recommendations view: This view is for individuals interested in gaining insight into how their current diet meets the daily recommended intake for each nutrient with recommendations on how to meet their daily needs. Within the Diet with Recommendations view users can select multiple foods and their nutrients of interest to receive visualization of that data. Additionally, in this view users will receive three recommended foods that are specifically selected to improve the nutrient content of the listed diet to meet dietary reference ranges. Dietary limitation and activity level information is not currently functional within this view.An example of this visualization is displayed below.
From d94738e23bfa7f644346b28c4605557982702c5f Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 11:35:05 -0500
Subject: [PATCH 12/28] Update README.md
---
README.md | 1 +
1 file changed, 1 insertion(+)
diff --git a/README.md b/README.md
index df5de9c..c2da631 100644
--- a/README.md
+++ b/README.md
@@ -30,6 +30,7 @@ Individual view: If a user was interested in viewing the nutrition content for a
[](https://postimg.cc/WqZxKTyt)
Comparison view: For users interested in viewing a nutrient comparison between multiple foods, the Comparison view allows for selection of various foods of interest and reports nutrient content. All nutrient options are consistent with those available in the Individual view, however this view is specifically color-coded to allow for consistent identification of what food item is contributing to each nutrient's daily recommended intake. This visualization can be seen here.
+
[](https://postimg.cc/nMm5nVdh)
Diet with Recommendations view: This view is for individuals interested in gaining insight into how their current diet meets the daily recommended intake for each nutrient with recommendations on how to meet their daily needs. Within the Diet with Recommendations view users can select multiple foods and their nutrients of interest to receive visualization of that data. Additionally, in this view users will receive three recommended foods that are specifically selected to improve the nutrient content of the listed diet to meet dietary reference ranges. Dietary limitation and activity level information is not currently functional within this view.An example of this visualization is displayed below.
From b4f0cf64c7975c43d32da182a75ccfb4b23de597 Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 11:36:26 -0500
Subject: [PATCH 13/28] Update README.md
---
README.md | 1 +
1 file changed, 1 insertion(+)
diff --git a/README.md b/README.md
index c2da631..92d3c85 100644
--- a/README.md
+++ b/README.md
@@ -35,6 +35,7 @@ Comparison view: For users interested in viewing a nutrient comparison between m
Diet with Recommendations view: This view is for individuals interested in gaining insight into how their current diet meets the daily recommended intake for each nutrient with recommendations on how to meet their daily needs. Within the Diet with Recommendations view users can select multiple foods and their nutrients of interest to receive visualization of that data. Additionally, in this view users will receive three recommended foods that are specifically selected to improve the nutrient content of the listed diet to meet dietary reference ranges. Dietary limitation and activity level information is not currently functional within this view.An example of this visualization is displayed below.
+[](https://postimg.cc/Cnw6vkbr)
All data on Dietary Reference Intakes are from the USDA (https://www.nal.usda.gov/sites/default/files/fnic_uploads/recommended_intakes_individuals.pdf) and are currently only applicable for individuals ages 19-30 years old.
From 43b80659c382ba4cf377609ad555ab9126704218 Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 11:36:54 -0500
Subject: [PATCH 14/28] Update README.md
---
README.md | 2 --
1 file changed, 2 deletions(-)
diff --git a/README.md b/README.md
index 92d3c85..24abedc 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,4 @@
# Visualizing the Nutritional Landscape of Food: an NIH Codeathon
-# links to any resulting DOI
-
# Problem
Dietary choices and nutrition behaviors are highly individual and change day to day. Many variables weigh heavily on a person's food choices:
From dc1cf9c3a28019293f101c8a470473e6ea7f8f7e Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 11:37:57 -0500
Subject: [PATCH 15/28] Update README.md
---
README.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/README.md b/README.md
index 24abedc..b4d8cd6 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,6 @@
# Visualizing the Nutritional Landscape of Food: an NIH Codeathon
-# Problem
+Problem
Dietary choices and nutrition behaviors are highly individual and change day to day. Many variables weigh heavily on a person's food choices:
- Access to food
- Work/school schedule
From ec18d7a79f0cb7a079019b8dc4294c8bf800671c Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 11:38:17 -0500
Subject: [PATCH 16/28] Update README.md
---
README.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/README.md b/README.md
index b4d8cd6..06e6540 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,6 @@
# Visualizing the Nutritional Landscape of Food: an NIH Codeathon
-Problem
+Problem
Dietary choices and nutrition behaviors are highly individual and change day to day. Many variables weigh heavily on a person's food choices:
- Access to food
- Work/school schedule
From 92d046966679ee30d60b008aa93e4db04d939fd5 Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 11:38:57 -0500
Subject: [PATCH 17/28] Update README.md
---
README.md | 16 ++++++++--------
1 file changed, 8 insertions(+), 8 deletions(-)
diff --git a/README.md b/README.md
index 06e6540..24913ff 100644
--- a/README.md
+++ b/README.md
@@ -16,11 +16,11 @@ All these factors make idenfitfying factual and unbiased information regarding n
*While it is largely difficult for scientific methods to account for all of the individual variations of diet preferences and access, information regarding nutritional content of food can be leveraged to develop data driven interpretations of foods.*
-# Our Solution
+Our Solution
Our primary aim for this project is to create an interactive visualization dashboard of a selection of foods and their nutritional contents (sourced from the United States Department of Agriculture (USDA) Food Data Central resource).
-# Visualization Dashboard
+Visualization Dashboard
You can reach our Streamlit dashboard here:https://share.streamlit.io/tantar/uncovering-the-nutritional-landscape-of-food/main/UNLF.py. Currently we support three different types of visualizations for individual foods, comparison between foods, and the user's personal diet with recommendations.
@@ -38,21 +38,21 @@ Diet with Recommendations view: This view is for individuals interested in gaini
All data on Dietary Reference Intakes are from the USDA (https://www.nal.usda.gov/sites/default/files/fnic_uploads/recommended_intakes_individuals.pdf) and are currently only applicable for individuals ages 19-30 years old.
-# For users of our Streamlit
+For users of our Streamlit
This freely available dashboard only requires internet access. Any individual who is interested in using the dashboard is able to interact with it on their local machine.
-# For those looking to replicate our Streamlit
+For those looking to replicate our Streamlit
First, an individual would need to download the datasets described in the "Datasets Used for this Project" section below. Once the foods and nutrient values are integrated into a single dataset, they would then need to calculate what percent of each nutrients recommended daily intakes it met by individual foods. If you are interested in skipping and using our aggregated dataset, it is made available in the data folder of our github. Individuals looking to replicate and edit the dashboard created for this project will need to download python and install the streamlit and plotly libraries. If interested in using our code, that is made readily available within our GitHub and can also be found in a condensed file on Zenodo. LINK
-# Future Directions
+Future Directions
We hope to continue refining our dashboard to include greater functionality and customization for users in a future codeathon. Our next steps for this project are to 1) increase the number of foods and nutrients our dashboard can reference, 2) automate updating of data from USDA FDC, 3) include macronutrients within the Diet + Recommendation view, 4) include all age bracket options for dietary reference intakes, 5) include activity level and dietary limitation specific customizations 6) allow for the serving size to be customized, and 7) pursue user testing and elicit feedback.
-# Datasets Used for this Project
+Datasets Used for this Project
- "Uncovering the Nutritional Landscape of Food by Kim" et al. [S1 Dataset. Foods analyzed in this study](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0118697#references)
- [USDA FoodData Central](https://fdc.nal.usda.gov/download-datasets.html) [April 2019 (CSV – 6.1MB)](https://fdc.nal.usda.gov/fdc-datasets/FoodData_Central_sr_legacy_food_csv_%202019-04-02.zip)
-# Our Team
+Our Team
Eric Ruan
Eva Jason - Postbaccalaureate IRTA in the NICHD
@@ -67,7 +67,7 @@ Adam Thomas
Dustin Moraczewski
-# References
+References
Kim S, Sung J, Foo M, Jin Y-S, Kim P-J (2015) Uncovering the Nutritional Landscape of Food. PLoS ONE 10(3): e0118697. https://doi.org/10.1371/journal.pone.0118697
From 5dc33ceea6621849d20c1fe066da2b72a58cce39 Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 11:42:22 -0500
Subject: [PATCH 18/28] Update README.md
---
README.md | 18 +++++++++---------
1 file changed, 9 insertions(+), 9 deletions(-)
diff --git a/README.md b/README.md
index 24913ff..927c607 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,6 @@
# Visualizing the Nutritional Landscape of Food: an NIH Codeathon
-Problem
+# Problem
Dietary choices and nutrition behaviors are highly individual and change day to day. Many variables weigh heavily on a person's food choices:
- Access to food
- Work/school schedule
@@ -16,11 +16,11 @@ All these factors make idenfitfying factual and unbiased information regarding n
*While it is largely difficult for scientific methods to account for all of the individual variations of diet preferences and access, information regarding nutritional content of food can be leveraged to develop data driven interpretations of foods.*
-Our Solution
+# Our Solution
Our primary aim for this project is to create an interactive visualization dashboard of a selection of foods and their nutritional contents (sourced from the United States Department of Agriculture (USDA) Food Data Central resource).
-Visualization Dashboard
+# Visualization Dashboard
You can reach our Streamlit dashboard here:https://share.streamlit.io/tantar/uncovering-the-nutritional-landscape-of-food/main/UNLF.py. Currently we support three different types of visualizations for individual foods, comparison between foods, and the user's personal diet with recommendations.
@@ -38,21 +38,21 @@ Diet with Recommendations view: This view is for individuals interested in gaini
All data on Dietary Reference Intakes are from the USDA (https://www.nal.usda.gov/sites/default/files/fnic_uploads/recommended_intakes_individuals.pdf) and are currently only applicable for individuals ages 19-30 years old.
-For users of our Streamlit
+# For users of our Streamlit
This freely available dashboard only requires internet access. Any individual who is interested in using the dashboard is able to interact with it on their local machine.
-For those looking to replicate our Streamlit
+# For those looking to replicate our Streamlit
First, an individual would need to download the datasets described in the "Datasets Used for this Project" section below. Once the foods and nutrient values are integrated into a single dataset, they would then need to calculate what percent of each nutrients recommended daily intakes it met by individual foods. If you are interested in skipping and using our aggregated dataset, it is made available in the data folder of our github. Individuals looking to replicate and edit the dashboard created for this project will need to download python and install the streamlit and plotly libraries. If interested in using our code, that is made readily available within our GitHub and can also be found in a condensed file on Zenodo. LINK
-Future Directions
+# Future Directions
We hope to continue refining our dashboard to include greater functionality and customization for users in a future codeathon. Our next steps for this project are to 1) increase the number of foods and nutrients our dashboard can reference, 2) automate updating of data from USDA FDC, 3) include macronutrients within the Diet + Recommendation view, 4) include all age bracket options for dietary reference intakes, 5) include activity level and dietary limitation specific customizations 6) allow for the serving size to be customized, and 7) pursue user testing and elicit feedback.
-Datasets Used for this Project
+# Datasets Used for this Project
- "Uncovering the Nutritional Landscape of Food by Kim" et al. [S1 Dataset. Foods analyzed in this study](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0118697#references)
- [USDA FoodData Central](https://fdc.nal.usda.gov/download-datasets.html) [April 2019 (CSV – 6.1MB)](https://fdc.nal.usda.gov/fdc-datasets/FoodData_Central_sr_legacy_food_csv_%202019-04-02.zip)
-Our Team
+# Our Team
Eric Ruan
Eva Jason - Postbaccalaureate IRTA in the NICHD
@@ -67,7 +67,7 @@ Adam Thomas
Dustin Moraczewski
-References
+# References
Kim S, Sung J, Foo M, Jin Y-S, Kim P-J (2015) Uncovering the Nutritional Landscape of Food. PLoS ONE 10(3): e0118697. https://doi.org/10.1371/journal.pone.0118697
From 4b9227f5ed29ea03158e01abca3518fef8b5aaec Mon Sep 17 00:00:00 2001
From: tantar <69642120+tantar@users.noreply.github.com>
Date: Thu, 12 Aug 2021 12:44:09 -0400
Subject: [PATCH 19/28] Update README.md
---
README.md | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/README.md b/README.md
index 927c607..12ebd5a 100644
--- a/README.md
+++ b/README.md
@@ -12,7 +12,7 @@ The decision of what foods to eat is further complicated by
- The Internet (media, online forums, etc.)
- Social media
-All these factors make idenfitfying factual and unbiased information regarding nutrition an increasingly difficult task.
+All these factors make identifying factual and unbiased information regarding nutrition an increasingly difficult task.
*While it is largely difficult for scientific methods to account for all of the individual variations of diet preferences and access, information regarding nutritional content of food can be leveraged to develop data driven interpretations of foods.*
@@ -24,7 +24,7 @@ Our primary aim for this project is to create an interactive visualization dashb
You can reach our Streamlit dashboard here:https://share.streamlit.io/tantar/uncovering-the-nutritional-landscape-of-food/main/UNLF.py. Currently we support three different types of visualizations for individual foods, comparison between foods, and the user's personal diet with recommendations.
-Individual view: If a user was interested in viewing the nutrition content for a single food item, they can select the Individual Food option. Within this option, a food such as ocean perch can be evaluated for its carbohydrate, protein, and fiber content in comparison to USDA daily recommended intake, as well as a selection of nutrients including: Vitamins A, D, E, K, and C, B vitamins, calcium, copper, iron, magnesium, phosphorus, potassium, selenium, sodium, and zinc. An example of this visualization is shown below.
+Individual view: If a user was interested in viewing the nutrition content for a single food item, they can select the Individual Foods option. Within this option, a food such as ocean perch can be evaluated for its carbohydrate, protein, and fiber content in comparison to USDA daily recommended intake, as well as a selection of nutrients including: Vitamins A, D, E, K, and C, B vitamins, calcium, copper, iron, magnesium, phosphorus, potassium, selenium, sodium, and zinc. An example of this visualization is shown below.
[](https://postimg.cc/WqZxKTyt)
Comparison view: For users interested in viewing a nutrient comparison between multiple foods, the Comparison view allows for selection of various foods of interest and reports nutrient content. All nutrient options are consistent with those available in the Individual view, however this view is specifically color-coded to allow for consistent identification of what food item is contributing to each nutrient's daily recommended intake. This visualization can be seen here.
From abdaf20326a4c0950a4ba29ad85e17662017c2df Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 11:54:59 -0500
Subject: [PATCH 20/28] Update README.md
---
README.md | 6 ++++--
1 file changed, 4 insertions(+), 2 deletions(-)
diff --git a/README.md b/README.md
index 12ebd5a..468b09d 100644
--- a/README.md
+++ b/README.md
@@ -25,7 +25,8 @@ Our primary aim for this project is to create an interactive visualization dashb
You can reach our Streamlit dashboard here:https://share.streamlit.io/tantar/uncovering-the-nutritional-landscape-of-food/main/UNLF.py. Currently we support three different types of visualizations for individual foods, comparison between foods, and the user's personal diet with recommendations.
Individual view: If a user was interested in viewing the nutrition content for a single food item, they can select the Individual Foods option. Within this option, a food such as ocean perch can be evaluated for its carbohydrate, protein, and fiber content in comparison to USDA daily recommended intake, as well as a selection of nutrients including: Vitamins A, D, E, K, and C, B vitamins, calcium, copper, iron, magnesium, phosphorus, potassium, selenium, sodium, and zinc. An example of this visualization is shown below.
-[](https://postimg.cc/WqZxKTyt)
+
+[](https://postimg.cc/0zvFrg61)
Comparison view: For users interested in viewing a nutrient comparison between multiple foods, the Comparison view allows for selection of various foods of interest and reports nutrient content. All nutrient options are consistent with those available in the Individual view, however this view is specifically color-coded to allow for consistent identification of what food item is contributing to each nutrient's daily recommended intake. This visualization can be seen here.
@@ -33,7 +34,8 @@ Comparison view: For users interested in viewing a nutrient comparison between m
Diet with Recommendations view: This view is for individuals interested in gaining insight into how their current diet meets the daily recommended intake for each nutrient with recommendations on how to meet their daily needs. Within the Diet with Recommendations view users can select multiple foods and their nutrients of interest to receive visualization of that data. Additionally, in this view users will receive three recommended foods that are specifically selected to improve the nutrient content of the listed diet to meet dietary reference ranges. Dietary limitation and activity level information is not currently functional within this view.An example of this visualization is displayed below.
-[](https://postimg.cc/Cnw6vkbr)
+[](https://postimg.cc/62z5bVDy)
+[](https://postimg.cc/vxB8JgsX)
All data on Dietary Reference Intakes are from the USDA (https://www.nal.usda.gov/sites/default/files/fnic_uploads/recommended_intakes_individuals.pdf) and are currently only applicable for individuals ages 19-30 years old.
From 903489435bc85363897bb7a17841468eb106a527 Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 11:55:31 -0500
Subject: [PATCH 21/28] Update README.md
---
README.md | 1 +
1 file changed, 1 insertion(+)
diff --git a/README.md b/README.md
index 468b09d..0dea2d0 100644
--- a/README.md
+++ b/README.md
@@ -35,6 +35,7 @@ Comparison view: For users interested in viewing a nutrient comparison between m
Diet with Recommendations view: This view is for individuals interested in gaining insight into how their current diet meets the daily recommended intake for each nutrient with recommendations on how to meet their daily needs. Within the Diet with Recommendations view users can select multiple foods and their nutrients of interest to receive visualization of that data. Additionally, in this view users will receive three recommended foods that are specifically selected to improve the nutrient content of the listed diet to meet dietary reference ranges. Dietary limitation and activity level information is not currently functional within this view.An example of this visualization is displayed below.
[](https://postimg.cc/62z5bVDy)
+
[](https://postimg.cc/vxB8JgsX)
All data on Dietary Reference Intakes are from the USDA (https://www.nal.usda.gov/sites/default/files/fnic_uploads/recommended_intakes_individuals.pdf) and are currently only applicable for individuals ages 19-30 years old.
From 3dc2a8e415def7b164f9f4386397bc52c72754f9 Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 11:59:10 -0500
Subject: [PATCH 22/28] Update README.md
---
README.md | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git a/README.md b/README.md
index 0dea2d0..b23076f 100644
--- a/README.md
+++ b/README.md
@@ -24,15 +24,15 @@ Our primary aim for this project is to create an interactive visualization dashb
You can reach our Streamlit dashboard here:https://share.streamlit.io/tantar/uncovering-the-nutritional-landscape-of-food/main/UNLF.py. Currently we support three different types of visualizations for individual foods, comparison between foods, and the user's personal diet with recommendations.
-Individual view: If a user was interested in viewing the nutrition content for a single food item, they can select the Individual Foods option. Within this option, a food such as ocean perch can be evaluated for its carbohydrate, protein, and fiber content in comparison to USDA daily recommended intake, as well as a selection of nutrients including: Vitamins A, D, E, K, and C, B vitamins, calcium, copper, iron, magnesium, phosphorus, potassium, selenium, sodium, and zinc. An example of this visualization is shown below.
+**Individual view:** If a user was interested in viewing the nutrition content for a single food item, they can select the Individual Foods option. Within this option, a food such as ocean perch can be evaluated for its carbohydrate, protein, and fiber content in comparison to USDA daily recommended intake, as well as a selection of nutrients including: Vitamins A, D, E, K, and C, B vitamins, calcium, copper, iron, magnesium, phosphorus, potassium, selenium, sodium, and zinc. An example of this visualization is shown below.
[](https://postimg.cc/0zvFrg61)
-Comparison view: For users interested in viewing a nutrient comparison between multiple foods, the Comparison view allows for selection of various foods of interest and reports nutrient content. All nutrient options are consistent with those available in the Individual view, however this view is specifically color-coded to allow for consistent identification of what food item is contributing to each nutrient's daily recommended intake. This visualization can be seen here.
+**Comparison view:** For users interested in viewing a nutrient comparison between multiple foods, the Comparison view allows for selection of various foods of interest and reports nutrient content. All nutrient options are consistent with those available in the Individual view, however this view is specifically color-coded to allow for consistent identification of what food item is contributing to each nutrient's daily recommended intake. This visualization can be seen here.
[](https://postimg.cc/nMm5nVdh)
-Diet with Recommendations view: This view is for individuals interested in gaining insight into how their current diet meets the daily recommended intake for each nutrient with recommendations on how to meet their daily needs. Within the Diet with Recommendations view users can select multiple foods and their nutrients of interest to receive visualization of that data. Additionally, in this view users will receive three recommended foods that are specifically selected to improve the nutrient content of the listed diet to meet dietary reference ranges. Dietary limitation and activity level information is not currently functional within this view.An example of this visualization is displayed below.
+**Diet with Recommendations view:** This view is for individuals interested in gaining insight into how their current diet meets the daily recommended intake for each nutrient with recommendations on how to meet their daily needs. Within the Diet with Recommendations view users can select multiple foods and their nutrients of interest to receive visualization of that data. Additionally, in this view users will receive three recommended foods that are specifically selected to improve the nutrient content of the listed diet to meet dietary reference ranges. Dietary limitation and activity level information is not currently functional within this view.An example of this visualization is displayed below.
[](https://postimg.cc/62z5bVDy)
From f68312cf20065c9b8881137d6c5e499646e29c7b Mon Sep 17 00:00:00 2001
From: Kyle Pu <31393170+Kyle-Pu@users.noreply.github.com>
Date: Thu, 12 Aug 2021 10:16:38 -0700
Subject: [PATCH 23/28] Update README.md
---
README.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/README.md b/README.md
index b23076f..c496308 100644
--- a/README.md
+++ b/README.md
@@ -60,7 +60,7 @@ Eric Ruan
Eva Jason - Postbaccalaureate IRTA in the NICHD
-Kyle Pu
+Kyle Pu - Computer Science Undergrad at UCLA
Lauren Chan - PhD Candidate in Nutrition at Oregon State University
From 0324ad110b460d58d814bae704dd645251d7ebda Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 12:51:07 -0500
Subject: [PATCH 24/28] Update README.md
---
README.md | 11 +++++++----
1 file changed, 7 insertions(+), 4 deletions(-)
diff --git a/README.md b/README.md
index c496308..45e76d1 100644
--- a/README.md
+++ b/README.md
@@ -26,17 +26,20 @@ You can reach our Streamlit dashboard here:https://share.streamlit.io/tantar/unc
**Individual view:** If a user was interested in viewing the nutrition content for a single food item, they can select the Individual Foods option. Within this option, a food such as ocean perch can be evaluated for its carbohydrate, protein, and fiber content in comparison to USDA daily recommended intake, as well as a selection of nutrients including: Vitamins A, D, E, K, and C, B vitamins, calcium, copper, iron, magnesium, phosphorus, potassium, selenium, sodium, and zinc. An example of this visualization is shown below.
-[](https://postimg.cc/0zvFrg61)
+[](https://postimg.cc/Bj2w2JLn)
+[](https://postimg.cc/Lh7y7Jjs)
**Comparison view:** For users interested in viewing a nutrient comparison between multiple foods, the Comparison view allows for selection of various foods of interest and reports nutrient content. All nutrient options are consistent with those available in the Individual view, however this view is specifically color-coded to allow for consistent identification of what food item is contributing to each nutrient's daily recommended intake. This visualization can be seen here.
-[](https://postimg.cc/nMm5nVdh)
+[](https://postimg.cc/7JTNDNSZ)
+[](https://postimg.cc/bd20Z32z)
**Diet with Recommendations view:** This view is for individuals interested in gaining insight into how their current diet meets the daily recommended intake for each nutrient with recommendations on how to meet their daily needs. Within the Diet with Recommendations view users can select multiple foods and their nutrients of interest to receive visualization of that data. Additionally, in this view users will receive three recommended foods that are specifically selected to improve the nutrient content of the listed diet to meet dietary reference ranges. Dietary limitation and activity level information is not currently functional within this view.An example of this visualization is displayed below.
-[](https://postimg.cc/62z5bVDy)
-[](https://postimg.cc/vxB8JgsX)
+[](https://postimg.cc/bZGS5vHq)
+[](https://postimg.cc/zbNL3Fmf)
+[](https://postimg.cc/9wpQD6d8)
All data on Dietary Reference Intakes are from the USDA (https://www.nal.usda.gov/sites/default/files/fnic_uploads/recommended_intakes_individuals.pdf) and are currently only applicable for individuals ages 19-30 years old.
From 19f8aff34c921a577c0e4b12b86310c501f37924 Mon Sep 17 00:00:00 2001
From: Eric Ruan <57604698+ericr491@users.noreply.github.com>
Date: Thu, 12 Aug 2021 14:17:37 -0400
Subject: [PATCH 25/28] Update README.md
---
README.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/README.md b/README.md
index 45e76d1..315355e 100644
--- a/README.md
+++ b/README.md
@@ -59,7 +59,7 @@ We hope to continue refining our dashboard to include greater functionality and
- [USDA FoodData Central](https://fdc.nal.usda.gov/download-datasets.html) [April 2019 (CSV – 6.1MB)](https://fdc.nal.usda.gov/fdc-datasets/FoodData_Central_sr_legacy_food_csv_%202019-04-02.zip)
# Our Team
-Eric Ruan
+Eric Ruan - Computer Science Undergrad at SBU
Eva Jason - Postbaccalaureate IRTA in the NICHD
From 5094e57ead9ab6443944ee75cb2844a06bd15126 Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 13:41:33 -0500
Subject: [PATCH 26/28] Update README.md
---
README.md | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/README.md b/README.md
index 315355e..2cf05c8 100644
--- a/README.md
+++ b/README.md
@@ -69,9 +69,9 @@ Lauren Chan - PhD Candidate in Nutrition at Oregon State University
Tarek Antar - Postbaccalaurate IRTA in the NIA
-Adam Thomas
+Adam Thomas - NIMH
-Dustin Moraczewski
+Dustin Moraczewski - NIMH
# References
From 94a494979e87d3f446db81184dec7331737bb80f Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 13:42:05 -0500
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# Visualizing the Nutritional Landscape of Food: an NIH Codeathon
-# Problem
+# Our Problem
Dietary choices and nutrition behaviors are highly individual and change day to day. Many variables weigh heavily on a person's food choices:
- Access to food
- Work/school schedule
From 278300a0bd86de52d412fe934c8531b4a66fd993 Mon Sep 17 00:00:00 2001
From: Lauren <49169837+laurenechan@users.noreply.github.com>
Date: Thu, 12 Aug 2021 13:45:21 -0500
Subject: [PATCH 28/28] Update README.md
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First, an individual would need to download the datasets described in the "Datasets Used for this Project" section below. Once the foods and nutrient values are integrated into a single dataset, they would then need to calculate what percent of each nutrients recommended daily intakes it met by individual foods. If you are interested in skipping and using our aggregated dataset, it is made available in the data folder of our github. Individuals looking to replicate and edit the dashboard created for this project will need to download python and install the streamlit and plotly libraries. If interested in using our code, that is made readily available within our GitHub and can also be found in a condensed file on Zenodo. LINK
# Future Directions
-We hope to continue refining our dashboard to include greater functionality and customization for users in a future codeathon. Our next steps for this project are to 1) increase the number of foods and nutrients our dashboard can reference, 2) automate updating of data from USDA FDC, 3) include macronutrients within the Diet + Recommendation view, 4) include all age bracket options for dietary reference intakes, 5) include activity level and dietary limitation specific customizations 6) allow for the serving size to be customized, and 7) pursue user testing and elicit feedback.
+We hope to continue refining our dashboard to include greater functionality and customization for users in a future codeathon. Our next steps for this project are to 1) increase the number of foods and nutrients our dashboard can reference, 2) automate updating of data from USDA FDC, 3) include macronutrients within the Diet + Recommendation view, 4) include all age bracket options for dietary reference intakes, 5) include activity level specific customizations 6) allow for the serving size to be customized, and 7) pursue user testing and elicit feedback.
# Datasets Used for this Project
- "Uncovering the Nutritional Landscape of Food by Kim" et al. [S1 Dataset. Foods analyzed in this study](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0118697#references)