WebSort object by labels (along an axis). Returns a new DataFrame sorted by label if inplace argument is False, otherwise updates the original DataFrame and returns None. The axis along which to sort. The value 0 identifies the rows, and 1 identifies the columns. If not None, sort on values in specified index level (s). WebYou can take the sum of the dataframe along the first axis, sort_values and take the first n columns: df[df.sum(0).sort_values(ascending=False)[:2].index] Australia Austria 2024-01-30 9 0 2024-01-31 9 9 Share. Improve this answer. Follow ... python; pandas; dataframe; sorting; or ask your own question.
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WebApr 11, 2024 · 1 Answer. Sorted by: 1. There is probably more efficient method using slicing (assuming the filename have a fixed properties). But you can use os.path.basename. It will automatically retrieve the valid filename from the path. data ['filename_clean'] = data ['filename'].apply (os.path.basename) Share. Improve this answer. WebMay 4, 2024 · You can use the following syntax to quickly sort a pandas DataFrame by column names: df = df[[' column1 ', ' column4 ', ' column3 ', ' column2 ']] The following examples show how to use this syntax in practice. Example 1: Sort Pandas DataFrame by Column Names. The following code shows how to sort a pandas DataFrame by … curious george betsy and steve
pandas.DataFrame.sort_index — pandas 2.0.0 documentation
WebJul 14, 2016 · I know this is an old question but OP seems to have wanted to put NaN values at the beginning since the output they posted is already sorted. In that case, there's a parameter in sort_values that controls where to put NaN values: na_position. df = df.sort_values(by='DateTime1', ascending=True, na_position='first') WebDec 31, 2024 · df = df.sort_values(by='date',ascending=True,inplace=True) works to the initial df but after I did a groupby, it didn't maintain the order coming out from the sorted df. To conclude, I needed from the initial data frame these two columns. Sorted the datetime column and through a groupby using the month (dt.strftime('%B')) the sorting got … WebJun 8, 2016 · 2 Answers. You can first extract digits and cast to int by astype. Then sort_values of column sort and last drop this column: df ['sort'] = df ['product'].str.extract (' (\d+)', expand=False).astype (int) df.sort_values ('sort',inplace=True, ascending=False) df = df.drop ('sort', axis=1) print (df) product values 2 a10 15 5 a6 67 1 a5 20 4 a3 ... easy hawaiian meatballs with pineapple