w3resource

Merging DataFrames based on a common column in Pandas

Python Pandas Numpy: Exercise-7 with Solution

Merge two Pandas DataFrames based on a common column.

Sample Solution:

Python Code:

import pandas as pd

# Create two sample DataFrames
df1 = pd.DataFrame({'ID': [1, 2, 3], 'Name': ['Teodosija', 'Sutton', 'Taneli']})
df2 = pd.DataFrame({'ID': [2, 3, 4], 'Age': [25, 30, 22]})

# Merge DataFrames based on the 'ID' column
merged_df = pd.merge(df1, df2, on='ID')

# Display the merged DataFrame
print(merged_df)

Output:

   ID    Name  Age
0   2  Sutton   25
1   3  Taneli   30

Explanation:

In the exerciser above -

  • First we create two sample DataFrames, "df1" and "df2", with a common column 'ID'.
  • The pd.merge function is used to merge the DataFrames based on the 'ID' column.
  • The on='ID' parameter specifies the common column on which the merge operation is performed.
  • The resulting DataFrame (merged_df) contains columns from both DataFrames, and rows are matched based on the values in the 'ID' column.

Flowchart:

Flowchart: Merging DataFrames based on a common column in Pandas.

Python Code Editor:

Previous: Merging DataFrames based on a common column in Pandas.
Next: Filtering DataFrame rows by column values in Pandas using NumPy array.

What is the difficulty level of this exercise?

Test your Programming skills with w3resource's quiz.



Become a Patron!

Follow us on Facebook and Twitter for latest update.

It will be nice if you may share this link in any developer community or anywhere else, from where other developers may find this content. Thanks.

https://198.211.115.131/python-exercises/pandas_numpy/pandas_numpy-exercise-7.php