Append pandas dataframe is automatically displayed as float but wants int

Question

How do I get pandas to add an integer and save an integer data type? I understand that I can df.test.astype (int) into the entire column after entering the data, but if I can do this while I am adding the data, it seems like this will be the best way. Here is an example:

from bitstring import BitArray
import pandas as pd
df = pd.DataFrame()

test = BitArray('0x01')
test = int(test.hex)
print(test)
df = df.append({'test':test, 'another':5}, ignore_index=True)

print(df.test)
print(df.another)

Here is the result:

1
0    1.0
Name: test, dtype: float64
0    5.0
Name: another, dtype: float64

It changes integers to float.

Answer 1

This is because your original data frame is empty. Initialize it with some integer column.

df = pd.DataFrame(dict(A=[], test=[], another=[]), dtype=int)
df.append(dict(A=3, test=4, another=5), ignore_index=True)

---

If i did

df = pd.DataFrame()
df.append(dict(A=3, test=4, another=5), ignore_index=True)

Answer 2

: df.append , # 18359, append pandas 0.23.0.

, Pandas 0.23.0 .

Answer 3

Well, there are 2 workarounds I found.

1. Upgrading to pandas Version >= 0.23.0

2. But if you cannot change the version of pandas, for example, when working with working code, changing the version may affect other scripts / codes in the environment prod. therefore below one line is a quick workaround.

df = df.astype(int)