Project - 2 | Data Analysis with Python |
Download Source Code of this project (Rs.39) - https://rzp.io/l/project2sourcecode
Download - Complete Course Notes - Data Analyst Self Study Material (Rs.250) - https://datasciencelovers.graphy.com/...
Download Dataset File - https://datasciencelovers.graphy.com/...
Download - Python Pandas Notes ( Rs.50 ) - http://bit.ly/3KxMpgA
Enrol in our Udemy courses :
1. Python Data Analytics Projects - https://www.udemy.com/course/bigdata-...
2. Python For Data Science - https://www.udemy.com/course/python-f...
3. Numpy For Data Science - https://www.udemy.com/course/python-n...
Download - Source Codes of Project-1 and Project-2 (Rs.75) - https://datasciencelovers.graphy.com/...
Download Free Core Python Notes - https://datasciencelovers.graphy.com/...
----------------------------------------------------------
Watch demo of Self Study Material - • Data Analyst - Course Notes | Python,...
Outside India, PayPal for Self Study Material ($4) - [email protected]
----------------------------------------------------------
Contact Mail Id : [email protected]
----------------------------------------------------------
In this video, you will learn how to work on a real project of Data Analysis with Python. Questions are given in the project and then solved with the help of Python. It is a project of Data Analysis with Python or you can say, Data Science with Python.
The commands that we used in this project :
import pandas as pd -- To import Pandas library
pd.read_csv - To import the CSV file in Jupyter notebook
head() - It shows the first N rows in the data (by default, N=5)
shape - It shows the total no. of rows and no. of columns of the dataframe
df.isnull( ).sum( ) - It detects the missing values from each column of the dataframe.
fillna() - To fill the null values of a column with some particular value
value_counts - In a column, it shows all the unique values with their count. It can be applied to a single column only.
isin() - To show all records including particular elements
apply() - To apply a function along any axis of DF
------------------------------------------------------
Q. 1) Instruction ( For Data Cleaning ) - Find all Null Values in the dataset. If there is any null value in any column, then fill it with the mean of that column.
Q. 2) Question ( Based on Value Counts )- Check what are the different types of Make are there in our dataset. And, what is the count (occurrence) of each Make in the data ?
Q. 3) Instruction ( Filtering ) - Show all the records where Origin is Asia or Europe.
Q. 4) Instruction ( Removing unwanted records ) - Remove all the records (rows) where Weight is above 4000.
Q. 5) Instruction ( Applying function on a column ) - Increase all the values of 'MPG_City' column by 3.
-----------------------------------------------------------------------
You must check our other videos :
Project 8 - • Project - 8 | Data Analysis with Pyth...
Project 7 - • Project - 7 | Data Analysis with Pyth...
Project 6 - • Project - 6 | Data Analysis with Pyth...
Project 5 - • Project - 5 | Data Analysis with Pyth...
Project 4 - • Project - 4 | Data Analysis with Pyth...
Project 3 - • Project - 3 | Data Analysis with Pyth...
Project 1 - • Project - 1 | Data Analysis with Pyth...
#python #dataanalytics #datascience #project
