convert_dtype

convert_dtype

Description

Converts datatype of a feature to its original datatype. If the datatype of a feature is being represented as a string while the initial datatype is an integer or a float or even a datetime dtype. The convert_dtype() function iterates over the feature(s) in a pandas dataframe and convert the features to their appropriate datatype

Signature: ds.feature_engineering.convert_dtype(df)


Parameter:
---------------------------
df: DataFrame, Series

    Dataset to convert data type

Returns:
-----------------
    DataFrame or Series.

Example:

```python df = pd.DataFrame({'Name':['Tom', 'nick', 'jack'], 'Age':['20', '21', '19'], 'Date of Birth': ['1999-11-17','20 Sept 1998','Wed Sep 19 14:55:02 2000']}) df

Name Age Date of Birth 0 Tom 20 1999-11-17 1 nick 21 20 Sept 1998 2 jack 19 Wed Sep 19 14:55:02 2000

df.info()

RangeIndex: 3 entries, 0 to 2 Data columns (total 3 columns): Name 3 non-null object Age 3 non-null object Date of Birth 3 non-null object dtypes: object(3) memory usage: 76.0+ bytes

conv = convert_dtype(df) conv.info()

RangeIndex: 3 entries, 0 to 2 Data columns (total 3 columns): Name 3 non-null object Age 3 non-null int32 Date of Birth 3 non-null datetime64[ns] dtypes: datetime64ns, int32(1), object(1) memory usage: 88.0+ bytes

Type: function