Pandas DataFrame Gt Method

Introduction

In this lab, you will learn about the DataFrame.gt() method in the Pandas library. This method is used to compare a DataFrame with another element-wise and returns a DataFrame of boolean values as a result of the comparison.

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Skills Graph

Import the pandas library

To use the DataFrame.gt() method, you first need to import the pandas library. You can do this using the following code:

import pandas as pd

Create a DataFrame

Next, create a DataFrame to work with. You can use the following code as an example:

df=pd.DataFrame({"A":[200,500],"B":[60,250],"C":[150,1]})

Compare with a scalar using the DataFrame.gt() method

Now, let's compare the DataFrame with a scalar using the DataFrame.gt() method. This will return a new DataFrame with boolean values indicating whether each element is greater than the scalar. Use the following code:

print(df.gt(200))

Compare with a Series using the DataFrame.gt() method

Next, let's compare the DataFrame with a Series using the DataFrame.gt() method. This will return a new DataFrame with boolean values indicating whether each element in the DataFrame is greater than the corresponding element in the Series. Use the following code:

series = pd.Series([150, 200, 150])
print(df.gt(series,axis=0))

Compare with another DataFrame using the DataFrame.gt() method

Finally, let's compare the DataFrame with another DataFrame using the DataFrame.gt() method. This will return a new DataFrame with boolean values indicating whether each element in the first DataFrame is greater than the corresponding element in the second DataFrame. Use the following code:

df_1=pd.DataFrame({"A":[200,500],"B":[60,250],"C":[150,1]})
df_2=pd.DataFrame({"A":[200,550],"B":[65,251],"C":[100,10]})
print(df_1.gt(df_2))

Summary

In this lab, you learned about the DataFrame.gt() method in the Pandas library. You saw how to compare a DataFrame with a scalar, a Series, and another DataFrame using this method. By using the DataFrame.gt() method, you can conveniently perform element-wise comparisons in a DataFrame and obtain boolean results.