Joining DataFrame
In order to join the dataframe, we use .join() function this function is used for combining the columns of two potentially differently indexed DataFrames into a single result DataFrame.
Python Pandas Join Dataframe
# importing pandas module
import pandas as pd
# Define a dictionary containing employee data
data1 = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj'],
'Age':[27, 24, 22, 32]}
# Define a dictionary containing employee data
data2 = {'Address':['Allahabad', 'Kannuaj', 'Allahabad', 'Kannuaj'],
'Qualification':['MCA', 'Phd', 'Bcom', 'B.hons']}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data1,index=['K0', 'K1', 'K2', 'K3'])
# Convert the dictionary into DataFrame
df1 = pd.DataFrame(data2, index=['K0', 'K2', 'K3', 'K4'])
display(df, df1)
# joining dataframe
res = df.join(df1)
res
Output:
Joining two datasets
For more information, refer to our Pandas Merging, Joining, and Concatenating tutorial
For a complete guide on Pandas refer to our Pandas Tutorial.
Data Analysis with Python
In this article, we will discuss how to do data analysis with Python. We will discuss all sorts of data analysis i.e. analyzing numerical data with NumPy, Tabular data with Pandas, data visualization Matplotlib, and Exploratory data analysis.