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Here is the original post: Python Pandas update a dataframe value from another dataframe

df1 and df2 have the same data structure.

The original column order: assignee id issuetype key

The problem is that after runing the following code:

df1.set_index('key',inplace=True)
df1.update(df2.set_index('key'))
df1.reset_index()

The column order of df1 changed to this:

key assignee id issuetype

How can I recover the initial structure after update one dataframe with another dataframe? thanks.

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1 Answer 1

Reset to default
2

Change order by original columns by DataFrame.reindex:

cols = df1.columns
df1.set_index('key',inplace=True)
df1.update(df2.set_index('key'))
df1 = df1.reset_index().reindex(cols, axis=1)
print (df1)
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13 Comments

I tired it, it didn't work. The "Key" is still the first column.
@Ming - Sorry, answer was edited. cols is necessary use for variable
it didn't work on my side, here is my code: df1=pd.read_csv("update_1.csv") df2=pd.read_csv("update_2.csv") cols = df1.columns df1.set_index('key',inplace=True) df1.update(df2.set_index('key')) df1.reset_index().reindex(cols, axis=1)
@Ming - Is assigned back output? Like df1 = df1.reset_index().reindex(cols, axis=1) and then print (df1) ? Answer was edited.
Yes, the printed out structure is not recovered.
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