How to reset index of multiple pandas dataframes using a loop in python?
I have 17 dataframes in a list and I want to reset index for all of them using a loop.
Any help?
-
1in what structure you have multiple df eg.in list etcAkhilesh_IN– Akhilesh_IN2019-04-08 17:31:49 +00:00Commented Apr 8, 2019 at 17:31
-
Please show us some code so we can help you achieve what you seekDarkCygnus– DarkCygnus2019-04-08 17:32:11 +00:00Commented Apr 8, 2019 at 17:32
-
Yes, my dfs are in a listuser3021495– user30214952019-04-08 17:34:41 +00:00Commented Apr 8, 2019 at 17:34
Add a comment
|
3 Answers
This would be the simplest way imo:
#This list contains the names of all of your dataframes
list_dataframes = [foo1, foo2, foo3, ..... , foo17]
for dataframe in list_dataframes:
dataframe.reset_index(inplace=True)
2 Comments
Scott Boston
This will not change the dataframes in list_dataframes because
reset_index is not an inplace operation.
Andrew
Can't understand why if I use
df = df.reset_index() instead of dataframe.reset_index(inplace=True), it won't work...You need to remember that reset_index is not an inplace operation and you need to reassign or use the inplace parameter.
df1 = pd.DataFrame(index=np.arange(1,10))
df2 = pd.DataFrame(index=pd.date_range('2019-01-1', periods=10))
df3 = pd.DataFrame(index=[*'ABCDEFGHIJ'])
lofdfs = [df1, df2, df3]
for df in lofdfs:
df.reset_index(inplace=True)
Or, use list comprehension:
[df.reset_index(inplace=True) for df in lofdfs]
Comments
Pandas's documentation say:
reset_index: Reset the index of the DataFrame, and use the default one instead. If the DataFrame has a MultiIndex, this method can remove one or more levels.
This is util when you has complex dataframe, but if you has separate dataframes you can do like:
for df in dataframes:
df.reset_index(inplace=True)
1 Comment
Scott Boston
This will not change the df in dataframes, because
reset_index is not an inplace operation.