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Project - 2 | Data Analysis with Python | #DataScience | Cars Dataset

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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
* 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
* 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
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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.
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