Pandas DataFrame Clip Method

Introduction

In this lab, we will learn how to use the clip() method in the Pandas library to trim values in a DataFrame. The clip() method allows us to set upper and lower thresholds and assign values outside the boundaries to the boundary values. This can be useful when we want to limit the range of values in our DataFrame.

VM Tips

After the VM startup is done, click the top left corner to switch to the Notebook tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

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Skills Graph

Import the pandas library and create a DataFrame

First, let's import the pandas library and create a DataFrame.

import pandas as pd

## Create a dictionary with some sample data
data = {'col_1': [9, -3, 0, -1, 12], 'col_2': [-2, -7, -6, 8, -5]}

## Create a DataFrame from the dictionary
df = pd.DataFrame(data)

Display the original DataFrame

Let's display the original DataFrame to see the values before applying the clip() method.

print("------DataFrame--------")
print(df)

Use the clip() method with an upper threshold

Now, let's use the clip() method to trim values at an upper threshold. This means that any values above the specified upper threshold will be set to the threshold value itself.

## Trim values at an upper threshold of 6
clipped_df = df.clip(upper=6)

print("------After clipping the DataFrame--------")
print(clipped_df)

Use the clip() method with a lower threshold

Next, let's use the clip() method to trim values at a lower threshold. This means that any values below the specified lower threshold will be set to the threshold value itself.

## Trim values at a lower threshold of -1
clipped_df = df.clip(lower=-1)

print("------After clipping the DataFrame--------")
print(clipped_df)

Use the clip() method with both upper and lower thresholds

Lastly, let's use the clip() method to trim values at both an upper and lower threshold. This means that any values above the upper threshold will be set to the upper threshold value, and any values below the lower threshold will be set to the lower threshold value.

## Trim values at a lower threshold of -1 and an upper threshold of 6
clipped_df = df.clip(-1, 6)

print("------After clipping the DataFrame--------")
print(clipped_df)

Summary

In this lab, we learned how to use the clip() method in the Pandas library to trim values in a DataFrame. We saw how we can set upper and lower thresholds to limit the range of values in the DataFrame. This can be useful in data cleaning and processing tasks.