Feature: Query authors and respondents #18 #30
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| #### `zulip_report2_thread_lengths.csv` | ||
| TODO | ||
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| #### `zulip_report3_users.csv` |
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Added a "codebook" section to the README.md. I added a codebook for the most recent report, but I need to do so for the rest of the outputs. See: #31
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| 3. The Zulip chat we're querying: https://chat.fhir.org/# | |||
| 4. Category keywords google sheet: | |||
| https://docs.google.com/spreadsheets/d/1OB0CEAkOhVTN71uIhzCo_iNaiD1B6qLqL7uwil5O22Q/edit#gid=1136391153 | |||
| 5. User roles google sheet: | |||
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@rohaher Just FYI, Davera and I decided to open up a new tab on the google sheet, where she'll put "user" -> "HL7 organization role" mappings.
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| 'zuliprc_path': os.path.join(ENV_DIR, '.zuliprc'), # rc = "runtime config" | |||
| 'chat_stream_name': 'terminology', | |||
| 'num_messages_per_query': 1000, | |||
| 'outpath_report1': os.path.join(PROJECT_DIR, 'zulip_report1_counts.csv'), | |||
| 'outpath_report2': os.path.join(PROJECT_DIR, 'zulip_report2_thread_lengths.csv'), | |||
| 'outpath_user_info': os.path.join(PROJECT_DIR, 'zulip_user_info.csv'), | |||
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As we create more and more outputs, I wonder if I should think more about how these outputs are named / organized.
| return df_report | ||
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| def create_report_users(df: pd.DataFrame) -> Tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]: |
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@rohaher I just wanted to share with you the new function I made to handle this feature. I feel like it is really repetitive, though; not very proud of it. Due for a refactor at some point.
| user_participation_df.to_csv(CONFIG['outpath_raw_results_user_participation'], index=False) | ||
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| # TODO: I really don't like how repetitive this is; even worse than previous block | ||
| # TODO: Have aggregated to keyword, category, and stream, but not to role agnostic of stream. Would be useful to add |
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Some other updates I'm thinking of making:
TODO: Have aggregated to keyword, category, and stream, but not to role agnostic of stream. Would be useful to add this, once streams feature is complete.
TODO: aggregate to agnostic of role? for every level? stream, category, keyword? If so, can call 'participant'
- Add: New function implementing basic feature: create_report_users_and_roles() - Add: Documentation for feature to README.md Misc - Add: Codebook section at bottom of README.md documentation. - Add: Comment link to user roles GoogleSheet. - Update: Renamed 'report1' and 'report2' variable and function names to be more descriptive. - Update: Reorganized run() - Update: Fixed an incorrect type. - Update: .gitignore: Added *.pickle
| return df_report | ||
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| def create_report_users(df: pd.DataFrame) -> Tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]: | ||
| """Report: Users | ||
| # TODO: Bugfix: Major bug; respondent/author counts are not all correct. This is because (i) threads are being |
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@rohaher FYI: Major bugfix I need to do:
# TODO: Bugfix: Major bug; respondent/author counts are not all correct. This is because (i) threads are being
counted multiple times when multiple keywords are matched against them, and (ii) we are *only* counting messages
within threads that have keyword matches; not every message in every thread that has a keyword match for any
message.
Updates