Question

You will create a new project. Type in the following program and run it to produce the output for the program. Good practice in writing a program in any language, including Python, is to add comments for each line and state clearly what is the program input and output. Your program must include comments, so a reader will know exactly what you are trying to do in each line of code and allow for easy maintenance. Beginning a line with a hash (#) character results in a single line comment and automatically terminated by the end of line. Comments that span multiple lines can be created by adding a triple quote (""") on each end of the block of comments. You will use PyCharm Edu to run the following Python program. The process must finish with exit code 0.

#BEGIN

""" Program Begin HERE
Some data Exploration using Python. Assuming that all the needed packages
are already install for your IDE to find them.
"""
#############################################################
#Program name - Data Exploration
#input - NONE
#output - Some Exploration statistics
###############################################################
import pandas as pd

# Create data_frame of array values
df = pd.DataFrame({
    'name':['matt','lisa','richard','john','Julia','jane','marlon'],
    'age':[23,78,22,19,45,33,20],
    'gender':['M','F','M','M','M','F','M'],
    'state':['DC','CO','DE','VA','MD','DE','NY'],
    'years_of_service':[10,0,2,0,2,1,5],
    'iq':[300,100,110,200,300,10,40]
})
########################################################
# BEGIN extract a 25% sample of data
########################################################
rows = df.sample(frac =.25)
# validate first to check if sample is 0.25 times data or not
if (0.25*(len(df))== len(rows)):
    print(len(df), len(rows))

# Display Sample Percentage
print 'sample of 25%',rows

#END extract a 25% sample of data
############################################################
# BEGIN Split categorical variables by gender, Sum, Mean, count,
# and describe on the data
############################################################

#Categorical Variables splitting
groupby_gender = df.groupby('gender')
for gender, value in groupby_gender['iq']:
    print((gender, value.mean()))

# Find the Summation of all ages in the data
SumofAge=df['age'].sum()
print 'Sum of Ages', SumofAge

MeanAge = df['age'].mean()
print 'Average Ages', MeanAge
# Find the mean of all columns
print ('Means of each column', df.mean(axis=0))
# Describe the Data
print df['iq'].describe()

#END

I keep getting an exit code of 1 saying line 32 is wrong! Help?

Answer 1

Python modified code:

#BEGIN

""" Program Begin HERE

Some data Exploration using Python. Assuming that all the needed packages

are already install for your IDE to find them.

"""

#############################################################

#Program name - Data Exploration

#input - NONE

#output - Some Exploration statistics

###############################################################

import pandas as pd

# Create data_frame of array values

df = pd.DataFrame({

'name':['matt','lisa','richard','john','Julia','jane','marlon'],

'age':[23,78,22,19,45,33,20],

'gender':['M','F','M','M','M','F','M'],

'state':['DC','CO','DE','VA','MD','DE','NY'],

'years_of_service':[10,0,2,0,2,1,5],

'iq':[300,100,110,200,300,10,40]

})

########################################################

# BEGIN extract a 25% of sample data

########################################################

rows = df.sample(frac =.25)

# validate first to check if sample is 0.25 times data or not

if (0.25*(len(df))== len(rows)):

print(len(df), len(rows))

# Display Sample Percentage

print ("Sample of 25%\n")

print(rows)

#END extract a 25% sample of data

############################################################

# BEGIN Split categorical variables by gender, Sum, Mean, count,

# and describe on the data

############################################################

#Categorical Variables splitting

groupby_gender = df.groupby('gender') #Grouping dataframe by 'gender'

for gender, value in groupby_gender['iq']:

print((gender, value.mean())) #print gender,corresponding mean

# Find the Summation of all ages in the data

SumofAge=df['age'].sum()

print ('Sum of Ages '+ str(SumofAge))

MeanAge = df['age'].mean()

print ('Average Ages ', str(MeanAge))

# Find the mean of all columns

print ('Means of each column ',str(df.mean(axis=0)))

# Describe the Data

print (df['iq'].describe())

#END

Python code Implementation:

OUTPUT:

NOTE:

# Beware of the indentation while copying the code into editor

# Any clarifications regarding this question can be asked in the comments section