How to plot simple moving averages with stock data

I am trying to plot simple moving averages (SMA) using Apple’s stock price. I have lines below:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import seaborn as sns

sns.set(style='darkgrid', context='talk', palette='Dark2')

my_year_month_fmt = mdates.DateFormatter('%m/%y')

data = pd.read_csv('C:\AAPL.csv')

# tried to change the Date format, then its 'start_date' and 'end_date' but it doesn't work 
# data['Date'] = pd.to_datetime(data['Date'])

short_rolling = data.rolling(window=20).mean()
long_rolling = data.rolling(window=100).mean()

start_date = '1/4/2010'
end_date = '12/31/2019'

fig, ax = plt.subplots(figsize=(16,9))

ax.plot(data.loc[start_date:end_date, :].index, data.loc[start_date:end_date, 'Close'], label='Price')
ax.plot(long_rolling.loc[start_date:end_date, :].index, long_rolling.loc[start_date:end_date, 'Close'], label = '100-days SMA')
ax.plot(short_rolling.loc[start_date:end_date, :].index, short_rolling.loc[start_date:end_date, 'Close'], label = '20-days SMA')

ax.legend(loc='best')
ax.set_ylabel('Price in $')
ax.xaxis.set_major_formatter(my_year_month_fmt)

plt.show()

But the plotting isn’t successful.

What did I do wrong, and how I can correct it?

Answer

From the code you posted, it seems as though you didn’t set the index of the dataframe after loading the data from the csv file. pd.read_csv does not by default assume the first column is the index.

If you had tried data.head() you would have noticed that Pandas adds a default index:

         Date  Open  High   Low  Close     Volume Currency
0  2010-01-04  7.62  7.66  7.58   7.64  493728704      USD
1  2010-01-05  7.66  7.70  7.62   7.66  601904640      USD
2  2010-01-06  7.66  7.69  7.53   7.53  552158912      USD
3  2010-01-07  7.56  7.57  7.47   7.52  477129760      USD
4  2010-01-08  7.51  7.57  7.47   7.57  447876768      USD

Thus, none of the subsequent df.loc methods found any data that matched the dates you provide as strings.

The following worked for me.

I replaced the line

data = pd.read_csv('C:\AAPL.csv')

with

data = pd.read_csv('AAPL.csv')
data['Date'] = pd.to_datetime(data['Date'])
data = data.set_index('Date')

and this is the output I get: