Joining a DataFrame to Another DataFrame Using Pandas Concat

What is Pandas?

Pandas is an open-source data analysis and manipulation library for the Python programming language. It provides data structures for efficiently storing and manipulating large datasets, as well as tools for data analysis, filtering, and visualization.

What is a DataFrame?

A DataFrame is a two-dimensional data structure in Pandas that is used for storing and manipulating tabular data. It is similar to a spreadsheet or a SQL table, where each column can have a different data type, and each row represents a unique record.

How to Join a DataFrame to Another DataFrame

To join one DataFrame to another DataFrame in Pandas, we use the concat() function. The concat() function takes two DataFrames as an argument and returns a new DataFrame with the joined data.

The syntax for using the concat() function is as follows:

new_dataframe = pd.concat([dataframe1, dataframe2])

Here, dataframe1 is the original DataFrame, and dataframe2 is the DataFrame that we want to combine to dataframe1. The concat() function returns a new DataFrame, which we store in the variable new_dataframe.

Let’s take a look at an example. Suppose we have two DataFrames, df1 and df2, which contain the following data:

import pandas as pd

# create df1
df1 = pd.DataFrame({
    'Name': ['Alice', 'Bob', 'Charlie'],
    'Age': [25, 30, 35],
    'City': ['New York', 'Los Angeles', 'Chicago']
})

# create df2
df2 = pd.DataFrame({
    'Name': ['Dave', 'Eve'],
    'Age': [40, 45],
    'City': ['Houston', 'Miami']
})

We can use the concat() function to combine df1 and df2 as follows:

# append df2 to df1
new_df = pd.concat([df1, df2])
print(new_df)

This will output:

       Name  Age          City
0     Alice   25      New York
1       Bob   30   Los Angeles
2   Charlie   35       Chicago
0      Dave   40       Houston
1       Eve   45         Miami

As you can see, the concat() function has combined df1 and df2 into a single DataFrame called new_df. The index values of df2 are preserved in new_df.

Conclusion

In this article, we have explored how to use the concat() function in Pandas to combine two data frames into a single data frame. The concat() function is a powerful tool for data manipulation in Pandas, and is especially useful for combining data frames with different structures or missing data. By following the steps outlined in this article, you can easily combine two data frames in Pandas and streamline your data analysis workflow.

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