a-pandas-ex-obj-into-cell 0.10

Puts objects into cells / columns of a Pandas Dataframe

Puts objects into cells / columns of a Pandas Dataframe

pip install a-pandas-ex-obj-into-cell

Not best (Pandas) practice, but sometimes very useful :)

from a_pandas_ex_obj_into_cell import pd_add_obj_into_cells

import pandas as pd



pd_add_obj_into_cells()

df = pd.read_csv(

    "https://raw.githubusercontent.com/pandas-dev/pandas/main/doc/data/titanic.csv"

)



d1 = df.d_one_object_to_several_cells(

    column="test1",

    value=({1: ("xx", 331, 11)}),

    indexlist=[1, 2, 3, 7],

    ffill=True,

    bfill=True,

)



print(d1)

d2 = df.d_list_items_to_cells(

    column="test2",

    values=[

        [

            1,

            32,

            4,

        ],

        {33: "dfd", 0: [3, 2]},

        4,

        (5, 34),

    ],

    indexlist=[1, 4, 6, 9],

    ffill=False,

    bfill=False,

)

print(d2)





'''     

PassengerId  Survived  Pclass  ... Cabin Embarked                 test1

0              1         0       3  ...   NaN        S  {1: ('xx', 331, 11)}

1              2         1       1  ...   C85        C  {1: ('xx', 331, 11)}

2              3         1       3  ...   NaN        S  {1: ('xx', 331, 11)}

3              4         1       1  ...  C123        S  {1: ('xx', 331, 11)}

4              5         0       3  ...   NaN        S  {1: ('xx', 331, 11)}

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

886          887         0       2  ...   NaN        S  {1: ('xx', 331, 11)}

887          888         1       1  ...   B42        S  {1: ('xx', 331, 11)}

888          889         0       3  ...   NaN        S  {1: ('xx', 331, 11)}

889          890         1       1  ...  C148        C  {1: ('xx', 331, 11)}

890          891         0       3  ...   NaN        Q  {1: ('xx', 331, 11)}

[891 rows x 13 columns]

     PassengerId  Survived  Pclass  ... Cabin Embarked                   test2

0              1         0       3  ...   NaN        S                    <NA>

1              2         1       1  ...   C85        C              [1, 32, 4]

2              3         1       3  ...   NaN        S                    <NA>

3              4         1       1  ...  C123        S                    <NA>

4              5         0       3  ...   NaN        S  {33: 'dfd', 0: [3, 2]}

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

886          887         0       2  ...   NaN        S                     NaN

887          888         1       1  ...   B42        S                     NaN

888          889         0       3  ...   NaN        S                     NaN

889          890         1       1  ...  C148        C                     NaN

890          891         0       3  ...   NaN        Q                     NaN

[891 rows x 13 columns]'''