Creating Data Frames And Concatenating Them In Python

In this post, we will learn how to create data frames in Python and merging them vertically and horizontally.

CREATING A DATA FRAME

Creating a data frame includes

1. Making a data list
2. Converting the list into a data frame with specified column’s names

MAKING A DATA LIST

Let’s create a data frame named ‘df_A’.

import pandas as pd

list_A = [('Mary',18),('Josh', 25),('Ryan',30)]

CONVERTING A DATA FRAME WITH SPECIFIED COLUMNS’S NAMES

df_A = pd.DataFrame(list_A, columns= ['Name', 'Age'])

Output:

Now let’s create a second data frame named ‘df_B’.

B = [('April', 22), ('Eileen', 18),('George', 22)]

df_B = pd.DataFrame(B, columns= ['Name', 'Age'])
df_B

Output:

CONCATENATING (MERGING) TWO DATA FRAMES

There are two different ways the data frames can be merged depending on the specific purpose. Vertical concatenating

• VERTICAL CONCATENATING

vertical_concat = pd.concat([df_A,df_B])

Output:

The two data frames df_A and df_B are merged vertically and the resulting vertical_concat data frame now contains six records.

HORIZONTAL CONCATENATING

Now let’s try horizontal concatenating using these two data frames.

horizontal_concat = pd.concat([df_A, df_B], axis=1)

Notice the usage of the axis=1 in here for horizontal concatenating.

Output: