copy-functions-and-more 0.10

Create an independent copy of any object, function etc.

Create an independent copy of any object, function etc.

pip install copy-functions-and-more 

from copy_functions_and_more import copy_func

import pandas as pd



df = pd.read_csv(    "https://github.com/pandas-dev/pandas/raw/main/doc/data/titanic.csv")

copieddescribe = copy_func(df.describe)

print(copieddescribe())

copy_func(df.__str__)

strco=copy_func(df.__str__)

print(strco())

print(copieddescribe is df.describe)

print(copieddescribe == df.describe)

print(strco is df.__str__)

print(strco == df.__str__)

       PassengerId    Survived      Pclass  ...       SibSp       Parch        Fare

count   891.000000  891.000000  891.000000  ...  891.000000  891.000000  891.000000

mean    446.000000    0.383838    2.308642  ...    0.523008    0.381594   32.204208

std     257.353842    0.486592    0.836071  ...    1.102743    0.806057   49.693429

min       1.000000    0.000000    1.000000  ...    0.000000    0.000000    0.000000

25%     223.500000    0.000000    2.000000  ...    0.000000    0.000000    7.910400

50%     446.000000    0.000000    3.000000  ...    0.000000    0.000000   14.454200

75%     668.500000    1.000000    3.000000  ...    1.000000    0.000000   31.000000

max     891.000000    1.000000    3.000000  ...    8.000000    6.000000  512.329200

[8 rows x 7 columns]

     PassengerId  Survived  Pclass  ...     Fare Cabin  Embarked

0              1         0       3  ...   7.2500   NaN         S

1              2         1       1  ...  71.2833   C85         C

2              3         1       3  ...   7.9250   NaN         S

3              4         1       1  ...  53.1000  C123         S

4              5         0       3  ...   8.0500   NaN         S

..           ...       ...     ...  ...      ...   ...       ...

886          887         0       2  ...  13.0000   NaN         S

887          888         1       1  ...  30.0000   B42         S

888          889         0       3  ...  23.4500   NaN         S

889          890         1       1  ...  30.0000  C148         C

890          891         0       3  ...   7.7500   NaN         Q

[891 rows x 12 columns]

False

False

False

False

newlist=[33354,442,4535,333]

newlist2=copy_func(newlist)

print(newlist2 is newlist)

print(newlist2 == newlist)  

False

True