Skip to content
Advertisement

Tag: pandas

Print side by side .describe() in pandas

Hello so i have two columns that im using describe() and im getting their stats. I have something like this I want to print desk1 and desk2 below of each category.I am doing this: I get this : And i my desired output is this: I would like to not create a dataframe.Any solutions? Thanks in advance Answer What about

Combining multiple CSVs in pandas

I have multiple csv files (which I’ve moved into pandas dataframes) in a folder, each of which holds monthly website data and need to combine them by copying the Value column from each to make a new dataframe (which will ultimately be exported to another csv) A new csv file will be added to the folder each month, so I

Concatenate columns at the end of a MultiIndex columns DataFrame

Consider the following DataFrames df : and df1: I want to concatenate the two DataFrames such that the resulting DataFrame is: What I run is pandas.concat([df1, df2, axis=1).sort_index(level=”kind”, axis=1) but that results in i.e. the column potato is appended at the beginning of df[“A”] whereas I want it appended to the end. Answer Add parameter sort_remaining=False in DataFrame.sort_index:

Collapsing rows

I have the following table below: I would like to collapse Code_1 and Code_2 columns based on ID and Date. Based on what I have found online, I have tried the below snippet of code but it does not seem to be working. df= df.groupby([‘ID’,’Date’]).agg(”.join) DF: ID Date Count_Code1 Count_Code2 Code_1 Code_2 A1 2022-02-02 90 0 AAAA NaN A1 2022-02-02

Advertisement