CODEWITHSUNDEEP
pythonpython-3.xcsvsumaverage
Anthony Harmon
Anthony Harmon

Reputation: 21

Reading a CSV file as Text File that performs Addition and Average

import csv                                                          
with open('Annual_Budget.csv') as csvfile:

readCSV = csv.reader(csvfile, delimiter=',')

Column_Sum = []
Third_Column_Avg = []
High_Value = []
Low_Value = []

for row in readCSV:
   Column_Sum = []
Third_Column_Avg = []
High_Value = []
Low_Value = []

Column_Sum.append(Column_Sum)
Third_Column_Avg.append(Third_Column_Avg)
High_Value.append(High_Value)
Low_Value.append(Low_Value)

print(Column_Sum)
print(Third_Column_Avg)
print(High_Value)
print(Low_Value)`

How to read a csv as a text file and for each row add up the all of the numeric columns, skipping any columns that cannot be perceived as numbers and displays the sum when it is completed. It must also display the average of all values in the third column. It must also display the highest value and lowest value from the second column and show which row these values appeared in. I put a mock annual budget in picture format so you can get the idea of what I am trying to accomplish. CSV SCREENSHOT EXAMPLE Output: [SUM OF ALL NUMERIC COLUMNS], [AVERAGE OF ALL VALUES IN THIRD COLUMN], [HIGHEST VALUE FROM SECOND COLUMN][LOWEST VALUE FROM SECOND COLUMN]

Upvotes: 2

Views: 60

Answers (1)

Jose Angel Sanchez
Jose Angel Sanchez

Reputation: 764

With the pandas library (I made a file just like your screenshot) if you don't have this library just pip install pandas

then 

In [1]: import pandas as pd

In [2]: my_file = pd.read_csv('stack.csv')

In [3]: my_file
Out[3]:
   anual budget    q2    q4
0            100  450    20
1            600  765    50
2            500  380    79
3            800  480   455
4           1100   65  4320

Anual budget, q2 and q4 sum 


my_file['anual budget '].sum() 
my_file['q2'].sum() 
my_file['q4'].sum()

Average of third column

my_file['q4'].mean()

Min and max value of second column 

my_file['q2'].max()
my_file['q2'].min()

Upvotes: 2

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