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Tag: pandas

Performing calculations on DataFrames of different lengths

I have two different DataFrames that look something like this: Lat Lon 28.13 -87.62 28.12 -87.65 …… …… Calculated_Dist_m 34.5 101.7 ………….. The first DataFrame (name=df) (consisting of the Lat and Lon columns) has just over 1000 rows (values) in it. The second DataFrame (name=new_calc_dist) (consisting of the Calculated_Dist_m column) has over 30000 rows (values) in it. I want to

vlookup in pandas python

I have two dataframes I want to check if a column from first dataframe contains values that are in the column of second dataframe, and if it does, create a column and add 1 to the row where it contains a value from first column first df: A header Another header First apple Second orange third banana fourth tea desired

Groupby mean doesn’t display all data

I want to see all the means of the numerical columns, grouped by position, using When I do this I only get 3 of the many columns The other columns are all integers or floats, and they have no NAs. If I do Then I get the correct output. How can I display weight using groupby? Thanks for any help

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