Python uses PyJanitor's to_ Datetime, to_ Numeric, to_ String and other functions for data conversion

Preparation work: 1. Install Python 3. x version and corresponding package manager, such as pip. 2. Create a new Python project and set up the Python interpreter. Dependent class libraries: 1. Pandas: Used for data processing and conversion. 2. PyJanitor: Used to extend the data conversion function of Pandas. Install dependent libraries: You can use the following command to install the required dependent libraries: python pip install pandas pyjanitor Data sample: To demonstrate PyJanitor's data conversion function, we use the following sample data: import pandas as pd data = { 'date': ['2020-01-01', '2020-02-01', '2020-03-01'], 'numeric': ['10', '20', '30'], 'string': ['apple', 'banana', 'orange'] } df = pd.DataFrame(data) The Dataframe is as follows: date numeric string 0 2020-01-01 10 apple 1 2020-02-01 20 banana 2 2020-03-01 30 orange Using PyJanitor for data conversion: python import pandas as pd import janitor data = { 'date': ['2020-01-01', '2020-02-01', '2020-03-01'], 'numeric': ['10', '20', '30'], 'string': ['apple', 'banana', 'orange'] } df = pd.DataFrame(data) #Convert date columns to date time type df = df.to_datetime('date', errors='coerce', format='%Y-%m-%d') #Convert numeric columns to numeric type df = df.to_numeric('numeric', errors='coerce') #Convert string columns to string type df = df.to_string('string') #Print the converted results print(df.dtypes) print(df) Output results: date datetime64[ns] numeric int64 string object dtype: object date numeric string 0 2020-01-01 10 apple 1 2020-02-01 20 banana 2 2020-03-01 30 orange Summary: PyJanitor is a Python library for data conversion that can extend the functionality of Pandas. It provides a series of convenient functions, such as' to '_ Datetime, to_ Numeric, to_ String `, etc., used to convert data to the specified type. Before using PyJanitor, it is necessary to ensure that Pandas and PyJanitor are installed, and then call relevant functions as needed.