In pandas.DataFrame.reset_index documentation here the functionality of 'level' parameter is written as: Only remove the given levels from the index. Removes all levels by default. But when i used the below code line: df.reset_index(level = 0) It did nothing
below are the result without & with level parameter.
>>df.reset_index(inplace = True)
index y proba y_cap
0 1664 1.0 0.899965 1
1 2099 1.0 0.899828 1
2 1028 1.0 0.899825 1
3 9592 1.0 0.899812 1
4 8324 1.0 0.899768 1
... ... ... ... ...
10095 8294 1.0 0.500081 1
10096 1630 1.0 0.500058 1
10097 7421 1.0 0.500058 1
10098 805 1.0 0.500047 1
10099 5012 1.0 0.500019 1
>>df.reset_index(level = 0, inplace = True)
index y proba y_cap
0 1664 1.0 0.899965 1
1 2099 1.0 0.899828 1
2 1028 1.0 0.899825 1
3 9592 1.0 0.899812 1
4 8324 1.0 0.899768 1
... ... ... ... ...
10095 8294 1.0 0.500081 1
10096 1630 1.0 0.500058 1
10097 7421 1.0 0.500058 1
10098 805 1.0 0.500047 1
10099 5012 1.0 0.500019 1
Also if running any of the below code blocks for 2nd time:
>>df.reset_index(inplace = True)
OR
>>df.reset_index(level = 0, inplace = True)
I get below output with level_0 column added to it?? with some random values in it.
level_0 index y proba y_cap
0 0 1664 1.0 1.0 1
1 3808 2280 1.0 1.0 1
2 3828 6394 1.0 1.0 1
3 3827 3410 1.0 1.0 1
4 3826 4992 1.0 1.0 1
... ... ... ... ... ...
10095 7193 5399 1.0 0.0 1
10096 7194 1801 1.0 0.0 1
10097 7195 3777 1.0 0.0 1
10098 7196 3314 1.0 0.0 1
10099 10099 5012 1.0 0.0 1
And again if I run the code for 3rd time it pops below error:
cannot insert level_0, already exists
Please let me understand the significance of level parameter & when it is used? As when i re-run my code it adds the level_0 column
The level parameter applies to DataFrames with multi-indexes.