I'm trying to apply a simple function on a pd.DataFrame but I need the index of each element while applying.
Consider this DataFrame:
| CLM_1 | CLM_1 | |
|---|---|---|
| A | foo | bar |
| B | bar | foo |
| C | bar | foo |
and I want a pd.Series as result like so:
A 'A'
B 'B'
C 'D'
Length: 3, dtype: object
My approach:
I used df.apply(lambda row: row.index, axis=1) which obviously didn't work.
Use to_series() on the index:
>>> df.index.to_series()
A A
B B
C C
dtype: object
If you want to use the index in a function, you can assign it as a column and then apply whatever function you need:
df["index"] = df.index
>>> df.apply(lambda row: row["CLM_1"]+row["index"], axis=1)
A fooA
B barB
C barC
dtype: object
Array.map & Array.foreach we have access to the value and it's index at the same time.(arr.map((item, index) => {...}))I used name attribute of the applying row and it worked just fine! no need to add more columns to my DataFrame.
df.apply(lambda row: row.name, axis=1)