Convert floats to ints in Pandas?

StackOverflow

I"ve been working with data imported from a CSV. Pandas changed some columns to float, so now the numbers in these columns get displayed as floating points! However, I need them to be displayed as integers, or, without comma. Is there a way to convert them to integers or not display the comma?

Answer rating: 264

To modify the float output do this:

df= pd.DataFrame(range(5), columns=["a"])
df.a = df.a.astype(float)
df

Out[33]:

          a
0 0.0000000
1 1.0000000
2 2.0000000
3 3.0000000
4 4.0000000

pd.options.display.float_format = "{:,.0f}".format
df

Out[35]:

   a
0  0
1  1
2  2
3  3
4  4

Answer rating: 220

Use the pandas.DataFrame.astype(<type>) function to manipulate column dtypes.

>>> df = pd.DataFrame(np.random.rand(3,4), columns=list("ABCD"))
>>> df
          A         B         C         D
0  0.542447  0.949988  0.669239  0.879887
1  0.068542  0.757775  0.891903  0.384542
2  0.021274  0.587504  0.180426  0.574300
>>> df[list("ABCD")] = df[list("ABCD")].astype(int)
>>> df
   A  B  C  D
0  0  0  0  0
1  0  0  0  0
2  0  0  0  0

EDIT:

To handle missing values:

>>> df
          A         B     C         D
0  0.475103  0.355453  0.66  0.869336
1  0.260395  0.200287   NaN  0.617024
2  0.517692  0.735613  0.18  0.657106
>>> df[list("ABCD")] = df[list("ABCD")].fillna(0.0).astype(int)
>>> df
   A  B  C  D
0  0  0  0  0
1  0  0  0  0
2  0  0  0  0




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