convert float to integer pandas
>>> df['C'] = df['C'].apply(np.int64)
>>> print(df)
... A B C D
... 0 8 0 1 6.226750
... 1 1 9 9 8.522808
... 2 1 4 2 7.739108convert float to integer pandas
>>> df['C'] = df['C'].apply(np.int64)
>>> print(df)
... A B C D
... 0 8 0 1 6.226750
... 1 1 9 9 8.522808
... 2 1 4 2 7.739108how to convert a pandas series from int to float in python
df['DataFrame Column'] = df['DataFrame Column'].astype(float)convert float to integer pandas
>>> 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 0object to int and float conversion pandas
In [39]:
df['2nd'] = df['2nd'].str.replace(',','').astype(int)
df['CTR'] = df['CTR'].str.replace('%','').astype(np.float64)
df.dtypes
Out[39]:
Date object
WD int64
Manpower float64
2nd int32
CTR float64
2ndU float64
T1 int64
T2 int64
T3 int64
T4 object
dtype: object
In [40]:
df.head()
Out[40]:
Date WD Manpower 2nd CTR 2ndU T1 T2 T3 T4
0 2013/4/6 6 NaN 2645 5.27 0.29 407 533 454 368
1 2013/4/7 7 NaN 2118 5.89 0.31 257 659 583 369
2 2013/4/13 6 NaN 2470 5.38 0.29 354 531 473 383
3 2013/4/14 7 NaN 2033 6.77 0.37 396 748 681 458
4 2013/4/20 6 NaN 2690 5.38 0.29 361 528 541 381convert float to integer pandas
>>> df['C'] = df['C'].apply(np.int64)
>>> print(df)
... A B C D
... 0 8 0 1 6.226750
... 1 1 9 9 8.522808
... 2 1 4 2 7.739108how to convert a pandas series from int to float in python
df['DataFrame Column'] = df['DataFrame Column'].astype(float)convert float to integer pandas
>>> 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 0object to int and float conversion pandas
In [39]:
df['2nd'] = df['2nd'].str.replace(',','').astype(int)
df['CTR'] = df['CTR'].str.replace('%','').astype(np.float64)
df.dtypes
Out[39]:
Date object
WD int64
Manpower float64
2nd int32
CTR float64
2ndU float64
T1 int64
T2 int64
T3 int64
T4 object
dtype: object
In [40]:
df.head()
Out[40]:
Date WD Manpower 2nd CTR 2ndU T1 T2 T3 T4
0 2013/4/6 6 NaN 2645 5.27 0.29 407 533 454 368
1 2013/4/7 7 NaN 2118 5.89 0.31 257 659 583 369
2 2013/4/13 6 NaN 2470 5.38 0.29 354 531 473 383
3 2013/4/14 7 NaN 2033 6.77 0.37 396 748 681 458
4 2013/4/20 6 NaN 2690 5.38 0.29 361 528 541 381Copyright © 2021 Codeinu
Forgot your account's password or having trouble logging into your Account? Don't worry, we'll help you to get back your account. Enter your email address and we'll send you a recovery link to reset your password. If you are experiencing problems resetting your password contact us
