Introduction
The DataFrame.from_records() method in Pandas is used to convert structured or record ndarray to a DataFrame. It can create a DataFrame object from a structured ndarray, sequence of tuples, or DataFrame.
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Import the necessary libraries
First, import the pandas and numpy libraries to use the functions and methods later in the code.
import pandas as pd
import numpy as np
Create a structured ndarray
Next, create a structured ndarray, which contains structured input data. This ndarray can be created by using the numpy.array function and specifying the data type for each field. For example:
data = np.array([(3, 'a'), (2, 'b'), (1, 'c'), (0, 'd')], dtype=[('col_1', 'i4'), ('col_2', 'U1')])
Convert ndarray to DataFrame
Use the DataFrame.from_records() method to convert the structured ndarray into a DataFrame. This method takes the structured ndarray as the input data and returns a DataFrame object. Assign the DataFrame object to a variable to be able to access and manipulate the DataFrame later. For example:
df = pd.DataFrame.from_records(data)
Display the DataFrame
Print the DataFrame to see the results. Using the print() function will display the DataFrame in a tabular format. For example:
print(df)
Summary
By following these steps, you can use the DataFrame.from_records() method in Pandas to convert a structured ndarray into a DataFrame. This method is useful when working with structured input data and allows for easy manipulation and analysis of the data using the powerful features of Pandas.