a-pandas-ex-string-to-dtypes 0.1

Convert a Pandas DataFrame/Series with dtype str/string/object to the best available dtypes

What is it used for?

Convert a Pandas DataFrame/Series with dtype str/string/object to the best available dtypes

Installation

pip install a-pandas-ex-string-to-dtypes

Usage

    from a_pandas_ex_string_to_dtypes import pd_add_string_to_dtypes

    import pandas as pd

    pd_add_string_to_dtypes()

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

    print(df)

    print(df.dtypes)   

    

    

         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]  

    

    PassengerId      int64

    Survived         int64

    Pclass           int64

    Name            object

    Sex             object

    Age            float64

    SibSp            int64

    Parch            int64

    Ticket          object

    Fare           float64

    Cabin           object

    Embarked        object

    dtype: object     

    

    

    

    

    

    dfstring = pd.concat(

        [df[x].astype("string") for x in df.columns], axis=1, ignore_index=True

    )

    dfstring.columns=df.columns

    print(dfstring)

    print(dfstring.dtypes)  

    

        PassengerId Survived Pclass  ...     Fare Cabin Embarked

    0             1        0      3  ...     7.25  <NA>        S

    1             2        1      1  ...  71.2833   C85        C

    2             3        1      3  ...    7.925  <NA>        S

    3             4        1      1  ...     53.1  C123        S

    4             5        0      3  ...     8.05  <NA>        S

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

    886         887        0      2  ...     13.0  <NA>        S

    887         888        1      1  ...     30.0   B42        S

    888         889        0      3  ...    23.45  <NA>        S

    889         890        1      1  ...     30.0  C148        C

    890         891        0      3  ...     7.75  <NA>        Q

    [891 rows x 12 columns]    

    

    

    PassengerId    string

    Survived       string

    Pclass         string

    Name           string

    Sex            string

    Age            string

    SibSp          string

    Parch          string

    Ticket         string

    Fare           string

    Cabin          string

    Embarked       string

    dtype: object    

    

    

    

    converted = dfstring.ds_string_to_best_dtype()

    print(converted)

    print(converted.dtypes)

         PassengerId  Survived  Pclass  ...     Fare Cabin Embarked

    0              1         0       3  ...   7.2500  <NA>        S

    1              2         1       1  ...  71.2833   C85        C

    2              3         1       3  ...   7.9250  <NA>        S

    3              4         1       1  ...  53.1000  C123        S

    4              5         0       3  ...   8.0500  <NA>        S

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

    886          887         0       2  ...  13.0000  <NA>        S

    887          888         1       1  ...  30.0000   B42        S

    888          889         0       3  ...  23.4500  <NA>        S

    889          890         1       1  ...  30.0000  C148        C

    890          891         0       3  ...   7.7500  <NA>        Q

    [891 rows x 12 columns]    

    

    

    PassengerId      uint16

    Survived          uint8

    Pclass            uint8

    Name             string

    Sex            category

    Age              object

    SibSp             uint8

    Parch             uint8

    Ticket           object

    Fare            float64

    Cabin          category

    Embarked       category

    dtype: object    

    

    

        Parameters:

            df: Union[pd.DataFrame, pd.Series]

        Returns:

            Union[pd.DataFrame, pd.Series]