Creating DataFrames from a list of lists with separately defined column names can be especially convenient when dealing with symmetrical data, such as when the number of rows and columns are the same (e.g., 3x3, 4x4, etc.).
This method allows for clear specification of both the column names and the data, enhancing readability and ease of understanding.
import pandas as pd
# Specify column names separately
column_names = ['A', 'B', 'C']
# Data as a list of lists
data = [
[1, 2, 3],
[4, 5, 6],
[7, 8, 9]
]
# Create DataFrame
df = pd.DataFrame(data, columns=column_names)
print(df)
Creating DataFrames from a list of lists with separately defined column names can be especially convenient when dealing with symmetrical data, such as when the number of rows and columns are the same (e.g., 3x3, 4x4, etc.).
This method allows for clear specification of both the column names and the data, enhancing readability and ease of understanding.