convert decimal to string python

Question

I imported tab delimited file to create a dataframe ( df ) which has the following label :

label
1
2

3

1

This is stored as pandas.core.series.Series and I want to convert it to string format so that I can get rid of the decimals when I write this out to a text file.

df.class_label=df.label.fillna('')
df.to_string(columns=['label'],index=False)

The variable type is still Series , and output (text file) also has the decimals:

1.0 2.0  3.0  1.0

How to get rid of these decimals?

Answer 1

您可以使用to_string()方法的float_format关键字参数：

df.to_string(columns=['label'], index=False, float_format=lambda x: '{:d}'.format(x))

Answer 2

Using astype(int) will change a float to an int and will drop your .0 as desired.

import pandas as pd
df = pd.DataFrame({'label': [1.0, 2.0, 4.0, 1.0]})
print(df)

    label
0   1.0
1   2.0
2   4.0
3   1.0

df.label = df.label.astype(int)
print(df)

    label
0   1
1   2
2   4
3   1

Here we do not need to convert this to a string. This will be done when exporting to .csv or .txt and will preserve the int .

Answer 3

I think you have some NaN values, so int are converted to float because na type promotions .

So you can read data in column label as str and then it works nice:

import pandas as pd
import numpy as np
import io

temp=u"""lab1;label
5;1
5;2
7;
7;3
"""
#after testing replace io.StringIO(temp) to filename
df = pd.read_csv(io.StringIO(temp), sep=';', dtype={'label':str})
print (df)
  lab1 label
0    5     1
1    5     2
2    7   NaN
3    7     3

df['class_label'] = df.label.fillna('')
print (df)
  lab1 label class_label
0    5     1           1
1    5     2           2
2    7   NaN            
3    7     3           3

print (df.to_string(columns=['class_label'],index=False))
class_label
         1
         2

         3