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Data analysis using Pandas

Last Updated : 11 Jul, 2025
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Pandas are the most popular python library that is used for data analysis. It provides highly optimized performance with back-end source code purely written in C or Python. 

We can analyze data in Pandas with:

Pandas Series

Series in Pandas is one dimensional(1-D) array defined in pandas that can be used to store any data type.

Creating Pandas Series

Python3 
# Program to create series # Import Panda Library import pandas as pd # Create series with Data, and Index a = pd.Series(Data, index=Index)

Here, Data can be:

  1. A Scalar value which can be integerValue, string
  2. A Python Dictionary which can be Key, Value pair
  3. A Ndarray

Note: Index by default is from 0, 1, 2, ...(n-1) where n is the length of data.  

Create Series from List

 Creating series with predefined index values.

Python3 
# Numeric data Data = [1, 3, 4, 5, 6, 2, 9] # Creating series with default index values s = pd.Series(Data) # predefined index values Index = ['a', 'b', 'c', 'd', 'e', 'f', 'g'] si = pd.Series(Data, Index)

Output:

Create Series from List
 
 

Create Pandas Series from Dictionary

Program to Create Pandas series from Dictionary.

Python3 
dictionary = {'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5} # Creating series of Dictionary type sd = pd.Series(dictionary)

Output:

Create Pandas Series from Dictionary
Dictionary type data

Convert an Array to Pandas Series

Program to Create ndarray series.

Python3 
# Defining 2darray Data = [[2, 3, 4], [5, 6, 7]] # Creating series of 2darray snd = pd.Series(Data)

Output:

Convert an Array to Pandas Series
Data as Ndarray

Pandas DataFrames

The DataFrames in Pandas is a two-dimensional (2-D) data structure defined in pandas which consists of rows and columns.

Creating a Pandas DataFrame

Python3 
# Program to Create DataFrame # Import Library import pandas as pd # Create DataFrame with Data a = pd.DataFrame(Data)

Here, Data can be:

  1. One or more dictionaries
  2. One or more Series
  3. 2D-numpy Ndarray

Create a Pandas DataFrame from multiple Dictionary

Program to Create a Dataframe with two dictionaries.

Python3 
# Define Dictionary 1 dict1 = {'a': 1, 'b': 2, 'c': 3, 'd': 4} # Define Dictionary 2 dict2 = {'a': 5, 'b': 6, 'c': 7, 'd': 8, 'e': 9} # Define Data with dict1 and dict2 Data = {'first': dict1, 'second': dict2} # Create DataFrame df = pd.DataFrame(Data) df

Output:

Create a Pandas DataFrame from multiple Dictionary
DataFrame with two dictionaries

Convert list of dictionaries to a Pandas DataFrame

Here, we are taking three dictionaries and with the help of from_dict() we convert them into Pandas DataFrame.

Python3 
import pandas as pd data_c = [ {'A': 5, 'B': 0, 'C': 3, 'D': 3}, {'A': 7, 'B': 9, 'C': 3, 'D': 5}, {'A': 2, 'B': 4, 'C': 7, 'D': 6}] pd.DataFrame.from_dict(data_c, orient='columns')

Output:

  A B C D 0 5 0 3 3 1 7 9 3 5 2 2 4 7 6

Create DataFrame from Multiple Series

Program to create a dataframe of three Series.

Python3 
import pandas as pd # Define series 1 s1 = pd.Series([1, 3, 4, 5, 6, 2, 9]) # Define series 2  s2 = pd.Series([1.1, 3.5, 4.7, 5.8, 2.9, 9.3]) # Define series 3 s3 = pd.Series(['a', 'b', 'c', 'd', 'e']) # Define Data Data ={'first':s1, 'second':s2, 'third':s3} # Create DataFrame dfseries = pd.DataFrame(Data) dfseries

Output:

Create DataFrame from Multiple Series
DataFrame with three series

Convert a Array to Pandas Dataframe

One constraint has to be maintained while creating a DataFrame of 2D arrays - The dimensions of the 2D array must be the same.

Python3 
# Program to create DataFrame from 2D array # Import Library import pandas as pd # Define 2d array 1 d1 =[[2, 3, 4], [5, 6, 7]] # Define 2d array 2 d2 =[[2, 4, 8], [1, 3, 9]] # Define Data Data ={'first': d1, 'second': d2} # Create DataFrame df2d = pd.DataFrame(Data) df2d

Output:

Convert a Array to Pandas Dataframe
DataFrame with 2d ndarray

A
Abhishek rajput
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