Category : filter

i am trying to filter this dataset with multiple conditions using loc The data is coming from an Excel file that I imported using df = pd.read_csv() Here is sample structure from the df using df.head() : df.head() need to filter on the following (columns) criteria: State-Gov, Bachelors, Never-Married, Adm-Clerical, Not-in-family, White, Male, United States, ..

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#This is what I do to filter the df: enter code here#start_date = ‘2021-08-12’ enter code here#end_date = ‘2021-09-11’ enter code here#after_start_date = data["savetime"] >= start_date enter code here#before_end_date = data["savetime"] <= end_date enter code here#between_two_dates = after_start_date & before_end_date enter code here#Aug_backups = data.loc[between_two_dates] #how can I make my program intelligent to capture month ..

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So Im picking apart this data set for different aggregations. I need to filter the set to only include rows from the month, prior to the current reporting month. I created all the date variables needed and they work: from datetime import date today = date.today() reportingyear = date.today().year reportingmonth = date.today().month – 1 reportingday ..

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This question seems super easy but I just can’t figure it out. I have the following dataframe: watched_df = pd.DataFrame([[‘Love Death Robots’, ‘2016-01-29 14:04:22’, ‘Anna’], [‘James Bond’, ‘2016-02-29 14:04:22’, ‘Anna’], [‘Lord of the Rings’, ‘2016-09-29 14:04:22’, ‘BoB’], [‘The Hobbit’, ‘2016-10-29 14:04:22’, ‘Anna’], [‘Beauty and the Beast’, ‘2016-06-29 14:04:22’, ‘BoB’]], columns=[‘Title’, ‘Date’, ‘Profile_Name’]) watched_df.head() For each ..

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