Calculates volume per trading day in the csv file and graphs it. Also writes down the exact volumes at each day to a txt file

volume.py

import pandas as pd
import numpy as np
import csv
import seaborn as sns
import matplotlib.pyplot as plt
import math

data = pd.read_csv("CL_June_2019.csv")

#new_data = data[59528000:59800000]
#print(new_data)
#new_data.to_csv("new_file.csv")
count = 0

volume = []
dict = {}
volume.append(data['Volume'])
volume.append(data['Date-Time'])
#print(volume[1][0][0:10])
for i in range(len(volume[0])):
    count += 1
    vol = volume[0][i]
    date = volume[1][i][5:10] #prints the whole date excluding the time
    if not math.isnan(vol):
        if date in dict:
            dict[date] += vol
        else:
            dict[date] = vol

    print(count)


#k = [keys for keys in dict]
#v = [dict[keys] for keys in dict]
keys = []
vals = []
for k,v in dict.items():
    keys.append(k)
    vals.append(v)
sns.barplot(x = keys,y =vals )
plt.xlabel("Date")
plt.ylabel('Volume')
plt.title("Volume")
plt.savefig("figuresomething2.png")
with open('volume2.txt','w') as file:
    for k,v in dict.items():
        #file.write(f"{k}: {int(v)} \n")
        file.write(str(k) + ": " + str(int(v)) + "\n")