Convert float64 column to int64 in Pandas

Question

I tried to convert a column from data type float64 to int64 using   df  column name   astype int64    but got an error      NameError  name  int64  is not defined   The column has number of people but was formatted as 7500000 0  any idea how I can simply change this float64 into int64

User · Accepted Answer

Solution for pandas 0 24  for converting numeric with missing values   df   pd DataFrame   column name   7500000 0 7500000 0  np nan    print  df  column name    0    7500000 0 1    7500000 0 2          NaN Name  column name  dtype  float64  df  column name     df  column name   astype np int64       ValueError  Cannot convert non-finite values  NA or inf  to integer    http   pandas pydata org pandas-docs stable user guide integer na html df  column name     df  column name   astype  Int64   print  df  column name    0    7500000 1    7500000 2        NaN Name  column name  dtype  Int64     I think you need cast to numpy int64   df  column name   astype np int64    Sample   df   pd DataFrame   column name   7500000 0 7500000 0    print  df  column name    0    7500000 0 1    7500000 0 Name  column name  dtype  float64  df  column name     df  column name   astype np int64   same as  df  column name     df  column name   astype pd np int64  print  df  column name    0    7500000 1    7500000 Name  column name  dtype  int64   If some NaNs in columns need replace them to some int  e g  0  by fillna  because type of NaN is float   df   pd DataFrame   column name   7500000 0 np nan     df  column name     df  column name   fillna 0  astype np int64  print  df  column name    0    7500000 1          0 Name  column name  dtype  int64   Also check documentation - missing data casting rules  EDIT   Convert values with NaNs is buggy   df   pd DataFrame   column name   7500000 0 np nan     df  column name     df  column name   values astype np int64  print  df  column name    0                7500000 1   -9223372036854775808 Name  column name  dtype  int64

User · Answer

You can need to pass in the string  int64     gt  gt  gt  import pandas as pd  gt  gt  gt  df   pd DataFrame   a    1 0  2 0       some test dataframe   gt  gt  gt  df  a   astype  int64   0    1 1    2 Name  a  dtype  int64   There are some alternative ways to specify 64-bit integers    gt  gt  gt  df  a   astype  i8          integer with 8 bytes  64 bit  0    1 1    2 Name  a  dtype  int64   gt  gt  gt  import numpy as np  gt  gt  gt  df  a   astype np int64     native numpy 64 bit integer 0    1 1    2 Name  a  dtype  int64   Or use np int64 directly on your column  but it returns a numpy array     gt  gt  gt  np int64 df  a    array  1  2   dtype int64

User · Answer

This seems to be a little buggy in Pandas 0 23 4   If there are np nan values then this will throw an error as expected   df  col     df  col   astype np int64    But doesn t change any values from float to int as I would expect if  ignore  is used   df  col     df  col   astype np int64 errors  ignore      It worked if I first converted np nan   df  col     df  col   fillna 0  astype np int64  df  col     df  col   astype np int64    Now I can t figure out how to get null values back in place of the zeroes since this will convert everything back to float again   df  col      df  col   replace 0 np nan

User · Answer

consider using   df  column name   astype  Int64    nan will be changed to NaN

[python] Convert float64 column to int64 in Pandas

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