Two Python Scripts

For a homework assignment we had to write a couple python scripts. The first analyzes monthly financial data to find the average monthly change, and the min and max changes along with their corresponding month. The second one can be used to count votes for an election and determine the winner. Both scripts output to a text file. The second one uses Pandas Data Frames. Both written using python 3. These and more are available on my github:
https://github.com/bendgame

Find Monthly Change:

import csv
import os

#fetch the file
file = os.path.join ('..', 'PyBank','PyBank_data.csv')

#create placeholder lists for the data
months = []
net_total = []

with open (file, newline = "") as csvfile:
    readcsv = csv.reader(csvfile, delimiter = ',')

    csv_header = next(csvfile)
    
    #put the data into lists
    for row in readcsv:
        months.append(row[0])
        net_total.append(int(row[1]))
        
    #count the number of months
    month_count = len(months)
    
    #set variables for loops
    x = 1
    y = 0
    
    #average change place holder
    average_change = (net_total[1]-net_total[0])
    
    #place holder list for changes 
    changes = []
    
    #for loop to calculate month to month change and dump the values into a list
    for month in range(month_count-1):
        average_change = (net_total[x] - net_total[y])
        changes.append(int(average_change))
        x+=1
        y+=1
        
    
    #Calcuate the average monthly change and round it    
    av_mon_chng = round(sum(changes)/(month_count -1),2)

    #find the min and max change
    min_change = min(changes)
    max_change = max(changes)

    #return the index to find the positions in the list
    chng_i_min = changes.index(min_change)
    chng_i_max = changes.index(max_change)
    
    #find the months for the min and max changes
    min_chng_month = months[chng_i_min + 1]
    max_chng_month = months[chng_i_max + 1]
  

#Print the values in console

print("Financial Analysis")
print("----------------------------")
print(f"Months: {len(months)}")
print(f"Total: ${sum(net_total)}")
print(f"Average Monthly Change: {av_mon_chng}")
print(f"Greatest Increase in Profits: {max_chng_month} (${max_change})")
print(f"Greatest Decrease in Profits: {min_chng_month} (${min_change})")

#Write the output to a text file
fin_analysis = open("Financial_Analysis.txt","w")

fin_analysis.write("Financial Analysis\n")
fin_analysis.write("----------------------------\n")
fin_analysis.write(f"Months: {len(months)}\n")
fin_analysis.write(f"Total: ${sum(net_total)}\n")
fin_analysis.write(f"Average Monthly Change: {av_mon_chng}\n")
fin_analysis.write(f"Greatest Increase in Profits: {max_chng_month} (${max_change})\n")
fin_analysis.write(f"Greatest Decrease in Profits: {min_chng_month} (${min_change})\n")

 
fin_analysis.close() 

Count votes and determine a winner:

import pandas as pd
import os

# Make a reference to the csv file path
csvfile = os.path.join ('..', 'PyPoll','election_data.csv')

# read the csv file as a DataFrame
elec_data = pd.read_csv(csvfile)

df_ed = pd.DataFrame(elec_data)

#create an empty list to store vote counts as percent
percent_count = []

#Create a list of unique(distinct) candidates
candidates = list(df_ed["Candidate"].unique())

#count the number of times the candidate appears and put into a list
counts = list(df_ed['Candidate'].value_counts())

#get the total vote count
total_votes = sum(counts)

#set variable for for loop
x = 0

#for loop to calculate percentages
for candidate in candidates:
    percentage = round(counts[x]/total_votes,3)
    percentage="{:.3%}".format(percentage)
    percent_count.append(percentage)
    x+=1

#create a zipped list of data to rebuild data frame
data = list(zip(candidates, percent_count, counts))

#calculate counts to find winner
max_count = df_ed['Candidate'].value_counts()

#find the most counts
winner_count = max_count.max()

#put the zipped data into a data frame
df_data = pd.DataFrame(data)

#search the data frame for the candidate with the most counts put it into a list
winner = list(df_data.loc[df_data[2]== winner_count,0])

#rename the columns for df_data
sorted_data =df_data.columns =["Candidate |", "Percent of Votes |", "Vote Count"]

#sort the columns by vote count in descending order for clean output
sorted_data = df_data.sort_values("Vote Count", ascending = False )

#print the output into console
print("Election Results")
print(" -------------------------")
print(f"Total Votes: {total_votes}")
print("--------------------------")
print(f"{sorted_data}")
print(f" -------------------------")
print(f"Winner: {winner}")
print(f"-------------------------")

#Write the outcome data to a txt file named election_winner

election_winner = open("election_winner.txt","w")

election_winner.write("Election Results\n")
election_winner.write("----------------------------\n")
election_winner.write(f"Total Votes: {total_votes}\n")
election_winner.write(f"--------------------------\n")
election_winner.write(f"{sorted_data}\n")
election_winner.write(f" -------------------------\n")
election_winner.write(f"Winner: {winner}\n")
election_winner.write(f"-------------------------")

election_winner.close()