Python – How to Create Dataframe using Numpy Array

0

In this post, you will get a code sample for creating a Pandas Dataframe using a Numpy array with Python programming.

Step 1: Load the Python Packages

import numpy as np
import pandas as pd

Step 2: Create a Numpy array

arr = np.array([[4, 7], [15,18], 
                [18,21], [13,19], 
                [10,15], [7,12], 
                [4,6], [5,9], [8,10], [9,14], [13,15], [11,12], [12,17]])

This is how the array would look like:

array([[ 4,  7],
       [15, 18],
       [18, 21],
       [13, 19],
       [10, 15],
       [ 7, 12],
       [ 4,  6],
       [ 5,  9],
       [ 8, 10],
       [ 9, 14],
       [13, 15],
       [11, 12],
       [12, 17]])

Step 3: Create a Transpose of Numpy Array

arr_tp = arr.transpose()

This is how the transpose would look like:

array([[ 4, 15, 18, 13, 10,  7,  4,  5,  8,  9, 13, 11, 12],
       [ 7, 18, 21, 19, 15, 12,  6,  9, 10, 14, 15, 12, 17]])

Step 4: Create a Pandas Dataframe

df = pd.DataFrame({'col1': arr_tp[0], 'col2': arr_tp[1]})

Print the data using head command such as df.head(). This is how the data frame would look like:

      col1	col2
0	4	7
1	15	18
2	18	21
3	13	19
4	10	15

In case, you would like to quickly plot the data and look for relationship, here are the command using seaborn package:

import seaborn as sns
sns.scatterplot(x=df['col1'], y=df['col2'])

The above would print the following plot:

Seaborn Scatterplot
Fig 1: Scatterplot representing the relationship between col1 and col2
Ajitesh Kumar

Ajitesh Kumar

Ajitesh has been recently working in the area of AI and machine learning. Currently, his research area includes Safe & Quality AI. In addition, he is also passionate about various different technologies including programming languages such as Java/JEE, Javascript and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data etc.

He has also authored the book, Building Web Apps with Spring 5 and Angular.
Ajitesh Kumar

Leave A Reply

Time limit is exhausted. Please reload the CAPTCHA.