Write a Pandas program to read a dataset from automobiles DataFrame and modify the default columns values and print the first 10 rows. b. Write a Pandas program to select a series from automobilesDataFrame. Print the content of the series. c. Write a Pandas program to create a new Company - Price' Series (use bracket notation to define the Series name) of the automobiles DataFrame d. Write a Pandas program to remove body style, engine type, length columns at once of the automobiles Dataframe e. Write a Pandas program to sort the entire automobiles DataFrame by the price Series in ascending and descending order. f. Write a Pandas program to find average price and change from nan to average price according to other automobiles of same company. g. Write a Pandas program to find the automobiles that are either hatchback or wagon. h. Write a Pandas program to read rows 0, 5, 7 and all columns of automobiles DataFrame. i. Write a Pandas program to calculate the memory usage for each Series (in bytes) of automobiles and total DataFrame and delete 3 feature which have maximum memory and calculate the memory usage for each Series (in bytes) of automobiles and total DataFrame.
a. Write a Pandas
columns values and print the first 10 rows.
b. Write a Pandas program to select a series from automobilesDataFrame. Print the content of the series.
c. Write a Pandas program to create a new Company - Price' Series (use bracket notation to define the
Series name) of the automobiles DataFrame
d. Write a Pandas program to remove body style, engine type, length columns at once of the automobiles
Dataframe
e. Write a Pandas program to sort the entire automobiles DataFrame by the price Series in ascending
and descending order.
f. Write a Pandas program to find average price and change from nan to average price according to other
automobiles of same company.
g. Write a Pandas program to find the automobiles that are either hatchback or wagon.
h. Write a Pandas program to read rows 0, 5, 7 and all columns of automobiles DataFrame.
i. Write a Pandas program to calculate the memory usage for each Series (in bytes) of automobiles and
total DataFrame and delete 3 feature which have maximum memory and calculate the memory usage for
each Series (in bytes) of automobiles and total DataFrame.
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