python pandas loops to melt or pivot multiple df

Question

I have several df with the same structure. I'd like to create a loop to melt them or create a pivot table.

I tried the following but are not working


my_df = [df1, df2, df3]

for df in my_df:
   df = pd.melt(df, id_vars=['A','B','C'], value_name = 'my_value')

for df in my_df:
   df = pd.pivot_table(df, values = 'my_value', index = ['A','B','C'], columns = ['my_column'])

Any help would be great. Thank you in advance

jezrael · Accepted Answer · 2020-09-23T11:24:54.700

2

You need assign output to new list of DataFrames:

out = []
for df in my_df:
   df = pd.melt(df, id_vars=['A','B','C'], value_name = 'my_value')
   out.append(df)

Same idea in list comprehension:

out = [pd.melt(df, id_vars=['A','B','C'], value_name = 'my_value') for df in my_df]

If need overwitten origional values in list:

for i, df in enumerate(my_df):
   df = pd.melt(df, id_vars=['A','B','C'], value_name = 'my_value')
   my_df[i] = df

print (my_df)

If need overwrite variables df1, df2, df3:

df1, df2, df3 = [pd.melt(df, id_vars=['A','B','C'], value_name = 'my_value') for df in my_df]

edited Sep 23 '20 at 11:24

answered Sep 23 '20 at 10:49

jezrael

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Thank you. What should I do if I want to keep df1, df2, df3 separate? Basically have three ouputs. – Matteo Sep 23 '20 at 11:17
@Matteo - Do you think output should be `[df1, df2, df3]` with melted data? – jezrael Sep 23 '20 at 11:18
@Matteo - So original data should be lost and overwitten? – jezrael Sep 23 '20 at 11:20
Yes original data should be lost and overwitten – Matteo Sep 23 '20 at 11:24
@Matteo - I think you can overwotten only list, `df1-df3` should be overitten by last solution. – jezrael Sep 23 '20 at 11:28
1

Thank you. The last solution (overwrite variables df1, df2, df3) is exactly what I needed. – Matteo Sep 23 '20 at 11:31

python pandas loops to melt or pivot multiple df

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