2888 Reshape Data: Concatenate

Problem Statement

DataFrame df1

Column Name	Type
student_id	int
name	object
age	int

DataFrame df2

Column Name	Type
student_id	int
name	object
age	int

Write a solution to concatenate these two DataFrames vertically into one DataFrame.

The result format is in the following example.

For the whole problem statement, please refer here.

Plans

• Use pandas to handle the data.

• Concatenate the two DataFrames vertically.

• Provide the concatenated DataFrame.

• The resulting DataFrame should have the same columns as the input DataFrames.

Solution

import pandas as pd

def concatenateTables(df1: pd.DataFrame, df2: pd.DataFrame) -> pd.DataFrame:
    # Concatenate df1 and df2
    return pd.concat([df1, df2], ignore_index=True)

Explanation

1. Import Pandas

   • We start by importing the Pandas library, which provides data structures and operations for manipulating numerical tables and time series.

2. Define the Function

   • We define a function concatenateTables that takes two arguments df1 and df2, which are DataFrames to be concatenated.

3. Concatenating DataFrames

   • We use the pd.concat function to concatenate the two DataFrames df1 and df2 vertically.

   • The ignore_index=True argument is used to reset the index of the resulting DataFrame after concatenation.

4. Return the Result

   • We return the concatenated DataFrame that contains the data from both input DataFrames vertically.