Concatenation in Pandas Python

Question

I am trying to concatenate these three columns, but the code i am using is giving me this output, i changed the format of all the columns to string:

Income_Status_Number   Income_Stability_Number  Product_Takeup_Number  Permutation
      1                      1                          2                1.012
      2                      1                          3                2.013
      1                      1                          1               1.011

this is the code i used:

df['Permutation']=df['Income_Status_Number'].astype(str)+""+df['Income_Stability_Number'].astype(str)+""+df['Product_Takeup_Number'].astype(str)

But I want my output to look like this:

Income_Status_Number   Income_Stability_Number  Product_Takeup_Number  Permutation
  1                      1                          2                     112
  2                      1                          3                     213
  1                      1                          1                     111

Please help.

Better is df['Permutation']=df['Income_Status_Number'].astype(str)+df['Income_Stability_Number'].astype(str)+df['Product_Takeup_Number'].astype(str), but it should working nice. — jezrael
– jezrael, Commented Jan 22, 2018 at 14:49
What's the purpose of adding "" between each concatenation? — A.Kot
– A.Kot, Commented Jan 22, 2018 at 14:53

Eric Ed Lohmar · Accepted Answer · 2018-01-22 16:01:43Z

1

The issue is that the first column is being treated as a float instead of an int. The simple way to solve this problem is to sum the values with multipliers to put the numbers is the correct space and let pandas realize that the number is an int:

df['Permutation'] = df['Income_Status_Number']*100 + df['Income_Stability_Number']*10 + df['Product_Takeup_Number']

Another solution is to use astype(int).astype to convert the number first, but that solution is somewhat slower:

10000 Runs Each

as_type
  Total: 9.7106s
  Avg: 971059.8162ns

Maths
  Total: 7.0491s
  Avg: 704909.3242ns

edited Jan 22, 2018 at 16:01

Eric Ed Lohmar

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answered Jan 22, 2018 at 15:05

PraneetNigam

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Comments

A.Kot · Accepted Answer · 2018-01-22 14:55:01Z

0

It looks like your first column is being read as a float right before you convert it to a string.

df['Permutation']=df['Income_Status_Number'].astype(int).astype(str)+df['Income_Stability_Number'].astype(int).astype(str)+df['Product_Takeup_Number'].astype(int).astype(str)

answered Jan 22, 2018 at 14:55

A.Kot

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DGav · Accepted Answer · 2018-01-22 14:59:01Z

0

Try the following code to add a 'Permutation' column to your data frame formatted in the way you wanted:

df['Permutation'] = df[df.columns[0:]].apply(lambda x: ''.join(x.dropna().astype(int).astype(str)),axis=1)

Which give you the following dataframe:

df
  Income_Status_Number Income_Stability_Number Product_Takeup_Number  \
0                    1                       1                     2
1                    2                       1                     3
2                    1                       1                     1

  Permutation
0         112
1         213
2         111

answered Jan 22, 2018 at 14:59

DGav

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Comments

Nayana Madhu · Accepted Answer · 2018-01-23 05:18:28Z

0

I hope this one will work for you.

df['Permutation'] = df[df.columns].apply(lambda x: ' '.join(x.dropna().astype(int).astype(str)),axis=1)

answered Jan 23, 2018 at 5:18

Nayana Madhu

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