Python Pandas Working With CSV's Hands-on Solution | TCS Fresco Play | Fresco Play

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Fresco Play Hands-on Python Pandas Working With CSV's

Task 1

 

•      Create a series named heights_A with values 176.2, 158.4, 167.6, 156.2, and 161.4. These values represent heights of 5 students of class A.

•      Label each student as s1, s2, s3, s4, and s5.

•      Create another series named weights_A with values 85.1, 90.2, 76.8, 80.4, and 78.9. These values represent weights of 5 students of class A.

•      Label each student as s1, s2, s3, s4, and s5.

•      Create a dataframe named df_A, which contains the height  and weight of five students namely s1, s2, s3, s4 and s5.

•      Label the columns

as Student_height and Student_weight,

respectively.

•      Write the contents of df_A to a CSV file named classA.csv.

Note:Use the to_csv method associated with a data frame.

•      Verify if the file classA.csv exists in the present directory using command Is -I.

•      You can also view the contents of the file using the command cat classA.csv

Click on Run then Install then write the below code in prog file. Then click Run then Run.

#Write your code here import numpy as np import pandas as pd

height_A=pd.Series([176.2, 158.4, 167.6, 156.2,161.4], index = ['s1', 's2', 's3', 's4', 's5'])

weight_A=pd.Series([85.1, 90.2, 76.8, 80.4, 78.9], index = ['s1', 's2', 's3', 's4', 's5']) df_A=pd.DataFrame({'Student_height':height_A, 'Student_weight':weight_A})

df_A.to_csv("classA.csv") df_A2=pd.read_csv("classA.csv") print(df_A2)

df_A3=pd.read_csv("classA.csv", index_col=0) print(df_A3)

np.random.seed(100)

heights_B = pd.Series(np.random.normal(loc= 170.0, scale=25.0, size=5)) np.random.seed(100)

weights_B=pd.Series(np.random.normal(loc= 75.0, scale=12.0, size=5))

df_B=pd.DataFrame({'Student_height':heights_B, 'Student_weight':weights_B}) df_B.to_csv("classB.csv", index=False)

df_B2=pd.read_csv("classB.csv")

print(df_B2)

df_B3=pd.read_csv("classB.csv", header=None) print(df_B3)

df_B4=pd.read_csv("classB.csv", header=None,skiprows=2) print(df_B4)

Run Test: Will be succesful