Big Data Analysis with Python
Project Video available on YouTube - https://youtu.be/fhiUl7f5DnI
📖 Get Python Data Analysis Self Study Notes - https://rzp.io/l/dslnotes239
In this project, 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.