During this week, you also started learning how as a Data Scientist, you will be required to write programs that perform python computations.
In this section, you will be required to create several python programs that should be able to perform the given operations then, display the results of the operations.
Take in two values from a user (both in pounds) then convert those values to kilograms.
Perform the sum of the values.
Perform the average of the values.
Find the difference between both values.
Find the quotient when one value is divided by the other.
Determine and print out whether any of the numbers are even or add.
Have comments applied appropriately.
Overview
In this section, you will act as a Data Science Consultant who will answer questions posed using a dataset collected by Dalberg. The dataset contains crops grown in Uganda.
SQL Programming Questions
Display a list of Sub Counties and their population and areas. Sort the list of districts by total crop area (descending order). Select only the Sub counties from the Moroto district, order them alphabetically and show their production of sorghum. Compute the total Maize production per District. Compute the number of Sub counties where Maize is produced and the total Maize production per District. Compute the overall Crop area in all Sub counties where population is over 20000. Sort the Maize production in descending order by Districts, only taking into account Sub counties where Maize area is larger than Sorghum area, and display the number of Sub counties per district matching that criteria. Dataset Description
This dataset contains yield and population per subcounty. The dataset for the above questions can be found here. [https://drive.google.com/a/moringaschool.com/file/d/1pWXDvs33OoULTH4kdzhGTUxJmp0dSgZq/view?usp=sharing].
The glossary for this table is as follows:
POP: total population for the subcounty S_Yield_Ha: average yield for sorghum for the subcounty (Kg/Ha) M_Yield_Ha: average yield for maize for the subcounty (Kg/Ha) Crop_Area_Ha: total crop area for the subcounty (Ha) S_Area_Ha: total sorghum crop area for the subcounty (Ha) M_Area_Ha: total maize crop area for the subcounty (Ha) S_Prod_Tot: total productivity for the sorghum for the subcounty (Kg) M_Prod_Tot: total productivity for the maize for the subcounty (Kg)
Overview
In this part of the assessment, you will be required to write a career development plan for your data science career. This will involve recording, reflecting, tracking, planning and reviewing the steps that you will take for the next five years of your data science career. Your career plan can take into account of any career path that you would want to undertake i.e. employment, entrepreneurship, consulting, etc.
You will be required to provide a write up (Google Docs Document) outlining your Data Science career plan. You can use the learnings from this week’s sessions.