ValueError: Cannot convert non-finite values (NA or inf) to integer in Python

Dung Do Tien Mar 19 2022 363

Hello guys. I just beginning learn Python 2 weeks. I am studying analysis data by using pandas package. I have created a program as below:

 import pandas as pd
import numpy as np

#create DataFrame
df = pd.DataFrame({'points': [22, 11, 13, 14, 17, 26, 29, 30],
                   'assists': [1, 9, 9, 6, 18, 8, 8, 6],
                   'rebounds': [12, np.nan, 12, 6, 4, np.nan, 8, 17]})
                   
df['rebounds'] = df['rebounds'].astype(int)
print(df) 

When running the code above I got an error ValueError: Cannot convert non-finite values (NA or inf) to integer.

 Traceback (most recent call last):
  File "HelloWorld.py", line 9, in <module>
    df['rebounds'] = df['rebounds'].astype(int)
  File "/usr/local/lib/python3.6/dist-packages/pandas/core/generic.py", line 5548, in astype
    new_data = self._mgr.astype(dtype=dtype, copy=copy, errors=errors,)
  File "/usr/local/lib/python3.6/dist-packages/pandas/core/internals/managers.py", line 604, in astype
    return self.apply("astype", dtype=dtype, copy=copy, errors=errors)
  File "/usr/local/lib/python3.6/dist-packages/pandas/core/internals/managers.py", line 409, in apply
    applied = getattr(b, f)(**kwargs)
  File "/usr/local/lib/python3.6/dist-packages/pandas/core/internals/blocks.py", line 595, in astype
    values = astype_nansafe(vals1d, dtype, copy=True)
  File "/usr/local/lib/python3.6/dist-packages/pandas/core/dtypes/cast.py", line 968, in astype_nansafe
    raise ValueError("Cannot convert non-finite values (NA or inf) to integer")
ValueError: Cannot convert non-finite values (NA or inf) to integer

I'm using Python 3.9.5 and Windows 11.

How can I fix it? Thanks for any suggestions.

Have 2 answer(s) found.
  • J

    Jesus Lopez Mar 19 2022

    Your array contains Nan or Null values. So it can not convert to int.

    I usually use fillna() method to help convert null /nan to 0 numbers. You can see the example below:

     import pandas as pd
    import numpy as np
    
    #create DataFrame
    df = pd.DataFrame({'points': [22, 11, 13, 14, 17, 26, 29, 30],
                       'assists': [1, 9, 9, 6, 18, 8, 8, 6],
                       'rebounds': [12, np.nan, 12, 6, 4, np.nan, 8, 17]})
                       
    df['rebounds'] = df['rebounds'].fillna(0) # Convert nan/null to 0
    df['rebounds'] = df['rebounds'].astype(int)
    print(df)

    #Output

         points  assists  rebounds
    0      22        1        12
    1      11        9         0
    2      13        9        12
    3      14        6         6
    4      17       18         4
    5      26        8         0
    6      29        8         8
    7      30        6        17 
  • E

    Erpcrew Agra Mar 19 2022

    This error is because your array has Nan values, it can not convert to integer.

    Solution: you can use dropna() method to help drop NAN or NULL values. See example: 

     import pandas as pd
    import numpy as np
    
    #create DataFrame
    df = pd.DataFrame({'points': [22, 11, 13, 14, 17, 26, 29, 30],
                       'assists': [1, 9, 9, 6, 18, 8, 8, 6],
                       'rebounds': [12, np.nan, 12, 6, 4, np.nan, 8, 17]})
                       
    df = df.dropna()
    df['rebounds'] = df['rebounds'].astype(int)
    print(df)

    #Output

      points  assists  rebounds
    0      22        1        12
    2      13        9        12
    3      14        6         6
    4      17       18         4
    6      29        8         8
    7      30        6        17

    I hope it helpful for you.

Leave An Answer
* NOTE: You need Login before leave an answer

* Type maximum 2000 characters.

* All comments have to wait approved before display.

* Please polite comment and respect questions and answers of others.

Popular Tips

X Close