Convert float64 column to int64 in Pandas

47

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?

This question is tagged with python pandas dataframe

~ Asked on 2017-05-13 18:01:51

The Best Answer is


79

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

~ Answered on 2017-05-13 18:03:10


6

You can need to pass in the string 'int64':

>>> import pandas as pd
>>> df = pd.DataFrame({'a': [1.0, 2.0]})  # some test dataframe

>>> df['a'].astype('int64')
0    1
1    2
Name: a, dtype: int64

There are some alternative ways to specify 64-bit integers:

>>> df['a'].astype('i8')      # integer with 8 bytes (64 bit)
0    1
1    2
Name: a, dtype: int64

>>> import numpy as np
>>> 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):

>>> np.int64(df['a'])
array([1, 2], dtype=int64)

~ Answered on 2017-05-13 18:09:20


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