Скачать или смотреть how to remove the rows which has non numeric data in python

Download this code from https://codegive.com
Title: How to Remove Rows with Non-Numeric Data in Python
Introduction:
In data analysis and manipulation tasks, you might often encounter datasets that contain mixed data types. It's essential to clean your data by removing rows that have non-numeric values in specific columns. This tutorial will guide you through the process of removing rows with non-numeric data from a DataFrame using Python, primarily focusing on the popular pandas library.
Prerequisites:
Step 1: Import the necessary libraries
Start by importing the required libraries, pandas in this case:
Step 2: Create or Load the DataFrame
You can create a DataFrame or load it from a CSV, Excel, or other data sources. For this tutorial, let's create a simple DataFrame:
Step 3: Remove Rows with Non-Numeric Data
Now, let's remove the rows from the DataFrame where any column contains non-numeric data. You can achieve this by using the pd.to_numeric function and errors='coerce' option, which converts non-numeric data to NaN and then using pd.dropna() to remove the rows with NaN values.
Explanation:
Step 4: Alternative Method - Keeping Only Numeric Rows
If you prefer to keep the rows with numeric data and discard the rest, you can achieve this with the pd.select_dtypes() function:
Conclusion:
In this tutorial, you learned how to remove rows with non