How do I add row indices to a column using lambda functions in Pandas?

Question

I have a dataframe as follows:

Original dataframe:

	Index	Value
0	aT	1
1	bee	2
2	cT	3
3	Y	4
4	D	5

I would like to combine each item in the "index" column (except items trailing with T), hyphen (-) and row number like this:

Expected result:

	Index	Value
0	aT	1
1	bee-1	2
2	cT	3
3	Y-3	4
4	D-4	5

My code is the following:

df = pandas.DataFrame({"Index": ["aT", "bee", "cT","Y","D"], "Value": [1, 2, 3,4,5]})
ind_name = df.iloc[df.index,0].apply(lambda x: x + '-' + str(df.index) if "T" not in x else x)

How to correct my code?

Chris · Accepted Answer · 2021-09-19 05:34:53Z

2

One way using pandas.Series.str.endswith and str.cat:

s = df["Index"]
df["Index"] = s.where(s.str.endswith("T"), 
                      s.str.cat(df.index.astype(str), "-"))
print(df)

Output:

   Index  Value
0     aT      1
1  bee-1      2
2     cT      3
3    Y-3      4
4    D-4      5

answered Sep 19, 2021 at 5:34

Chris

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Comments

Алексей Р · Accepted Answer · 2021-09-19 05:26:28Z

0

Solution with .apply:

import pandas as pd

df = pd.DataFrame({"Index": ["aT", "bee", "cT", "Y", "D"], "Value": [1, 2, 3, 4, 5]})
df['Index'] = df.apply(lambda x: x['Index'] + ('' if 'T' in x['Index'] else f'-{x.name}'), axis=1)
print(df)

Prints:

   Index  Value
0     aT      1
1  bee-1      2
2     cT      3
3    Y-3      4
4    D-4      5

answered Sep 19, 2021 at 5:26

Алексей Р

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Comments

U13-Forward · Accepted Answer · 2021-09-19 05:04:48Z

0

Try with loc with str.contains and += instead:

>>> df.loc[~df['Index'].str.contains('T'), 'Index'] += '-' + df.index.to_series().astype(str)
>>> df
   Index  Value
0     aT      1
1  bee-1      2
2     cT      3
3    Y-3      4
4    D-4      5
>>>

Remember to add to_series() so that pandas would be able to detect corresponding indexes and add to them, just a pure Index object does not have an index since it's values are the index :)

answered Sep 19, 2021 at 5:04

U13-Forward

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