Pandas to_csv hands on for data analysis - export-to-csv

Question

Question:
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 dataframe.
Verify if the file classA.csv exists in the present directory using command ls -l.
You can also view the contents of the file using the command cat classA.csv
My code:
import pandas as pd
heights_A = pd.Series([176.2, 158.4, 167.6, 156.2,161.4])
heights_A.index = ["S1","S2","S3","S4","S5"]
weights_A = pd.Series([85.1, 90.2, 76.8, 80.4, 78.9])
weights_A.index = ["S1","S2","S3","S4","S5"]
df_A = pd.DataFrame({'Student_height': heights_A,'Student_weight':weights_A}, index = weights_A.index)
df_A.to_csv("classA.csv")
while checking with ls -l and cat classA.csv I can see the expected contents yet the checker does not allow me to proceed. Not sure where I am wrong

Answer 1

Use small letters for s1,s2...
import pandas as pd
heights_A = pd.Series([176.2, 158.4, 167.6, 156.2,161.4])
heights_A.index = ["s1","s2","s3","s4","s5"]
print(heights_A[1])
weights_A = pd.Series([85.1, 90.2, 76.8, 80.4, 78.9])
weights_A.index = ["s1","s2","s3","s4","s5"]
df_A = pd.DataFrame({'Student_height': heights_A,'Student_weight':weights_A}, index = weights_A.index)
df_A.to_csv("classA.csv")

Answer 2

import os
import numpy as np
import pandas as pd
# Creating the Series
heights_A = pd.Series([ 176.2, 158.4, 167.6, 156.2, 161.4 ])
# Creating the row axis labels
heights_A.index = ['s1', 's2', 's3', 's4','s5']
# Creating the Series
weights_A = pd.Series([85.1, 90.2, 76.8, 80.4 , 78.9])
# Creating the row axis labels
weights_A.index = ['s1', 's2', 's3', 's4','s5']
df_A = pd.DataFrame()
df_A['Student_height'] = heights_A
df_A['Student_weight'] = weights_A
# Display the shape of dataframe df_A
df_A.shape
df_A = pd.DataFrame({'Student_height': heights_A,'Student_weight':weights_A}, index = weights_A.index)
df_A.to_csv("classA.csv")
os.system("cat 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)
x=np.random.normal(loc=170.0,scale=25.0,size=5)
np.random.seed(100)
heights_B=pd.Series(x,index=['s1','s2','s3','s4','s5'])
np.random.seed(100)
y=np.random.normal(loc=75.0,scale=12.0,size=5)
weights_B=pd.Series(y,index=['s1','s2','s3','s4','s5'])
df_B = pd.DataFrame({'Student_height': heights_B,'Student_weight':weights_B}, index = weights_B.index)
df_B.to_csv("classB.csv",index=False)
os.system("cat classB.csv")
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)