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Difference between Pandas VS NumPy

  • Difficulty Level : Easy
  • Last Updated : 24 Oct, 2020

Pandas: It is an open-source, BSD-licensed library written in Python Language. Pandas provide high performance, fast, easy to use data structures and data analysis tools for manipulating numeric data and time series. Pandas is built on the numpy library and written in languages like Python, Cython, and C. In pandas, we can import data from various file formats like JSON, SQL, Microsoft Excel, etc.

Example:

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Python3






# Importing pandas library
import pandas as pd
  
# Creating and initializing a nested list
age = [['Aman', 95.5, "Male"], ['Sunny', 65.7, "Female"],
       ['Monty', 85.1, "Male"], ['toni', 75.4, "Male"]]
  
# Creating a pandas dataframe
df = pd.DataFrame(age, columns=['Name', 'Marks', 'Gender'])
  
# Printing dataframe
df

Output:

Numpy: It is the fundamental library of python, used to perform scientific computing. It provides high-performance multidimensional arrays and tools to deal with them. A numpy array is a grid of values (of the same type) that are indexed by a tuple of positive integers, numpy arrays are fast, easy to understand, and give users the right to perform calculations across arrays.

Example:

Python3




# Importing Numpy package
import numpy as np
  
# Creating a 3-D numpy array using np.array()
org_array = np.array([[23, 46, 85],
                      [43, 56, 99],
                      [11, 34, 55]])
  
# Printing the Numpy array
print(org_array)

Output:

[[23 46 85]
[43 56 99]
[11 34 55]]

Table of Difference Between Pandas VS NumPy

 

PANDAS

NUMPY

1When we have to work on Tabular data, we prefer the pandas module.When we have to work on Numerical data, we prefer the numpy module.
2The powerful tools of pandas are Data frame and Series.Whereas the powerful tool of numpy is Arrays.
3Pandas consume more memory.Numpy is memory efficient.
4Pandas has a better performance when number of rows is 500K or more.Numpy has a better performance when number of rows is 50K or less.
5Indexing of the pandas series is very slow as compared to numpy arrays.Indexing of numpy Arrays is very fast.
6Pandas offers 2d table object called DataFrame.Numpy is capable of providing multi-dimensional arrays.



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