Apply Function On Each Column In A Pandas Dataframe

How I can write following function in more pandas way: def calculate_df_columns_mean(self, df): means = {} for column in df.columns.columns.tolist():

Solution 1:

It seems to me that the iteration over the columns is unnecessary:

defcalculate_df_columns_mean(self, df):
    cleaned_data = self.remove_outliers(df[column].tolist())
    return cleaned_data.mean()

the above should be enough assuming that remove_outliers still returns a df

EDIT

I think the following should work:

defcalculate_df_columns_mean(self, df):
    return df.apply(lambdax: remove_outliers(x.tolist()).mean()

Solution 2:

Use dataFrame.apply(func, axis=0):

# axis=0 means apply to columns; axis=1 to rows
df.apply(numpy.sum, axis=0) # equiv to df.sum(0)