How do I fix my left scale? Matplotlib and Pandas

I am trying to plot this data with matplotlib.

I am able to get all of the data and make a graph of jones vs time, but my scale becomes wacky when I try to use the falls data set.

The graph and code I created are below.

import gspread
from oauth2client.service_account import ServiceAccountCredentials
import pandas as pd
from pandas import DataFrame
import datetime as dt
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import numpy as np

scope = ['https://spreadsheets.google.com/feeds',
         'https://www.googleapis.com/auth/drive']

credentials = ServiceAccountCredentials.from_json_keyfile_name(
         'pandastest-273019-00f3c09845fb.json', scope) # Your json file here

gc = gspread.authorize(credentials)

wks = gc.open("data").sheet1

data = wks.get_all_values()
headers = data.pop(0)

df = pd.DataFrame(data, columns=headers)
pd.set_option("display.max_rows",None,"display.max_columns", None)
print(df.head())

dates = []
fort = []
jones = []
pat = []
ferry = []
middle = []
north = []
canton = []
for x in data[:]:
    for i in range(0, len(x)):
        try:
            x[i] = int(x[i])
        except:
            continue

    print(x)
    dates.append(x[0])
    fort.append(x[1])
    jones.append(x[2])
    pat.append(x[3])
    ferry.append(x[4])
    middle.append(x[5])
    north.append(x[6])
    canton.append(x[7])

#fort
x = [dt.datetime.strptime(d,'%m/%d/%Y').date() for d in dates]
plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%m/%d/%Y'))
plt.gca().xaxis.set_major_locator(mdates.DayLocator(interval=29))
plt.plot(x,fort)
plt.gcf().autofmt_xdate()
plt.legend(["fort", ])
plt.xlabel("Dates")
plt.ylabel("Matter")
plt.show()

Does anyone know why this is happening and how I can fix it?