This produces a graph of all these stock prices plotted against the date. If you zoom in, all the tiny ticks have labels for the dates. I wanted to reduce the frequency of ticks so that it only displayed tick marks at the month and year. I have tried using locators and formatters, but whenever I add them all of the ticks and tick labels completely disappear. All that's left at the x-axis is the x-axis label.
Does any of the issue lie within the fact that I extract the date and use that for the x-axis plot for every new batch of stock prices I want to plot? Any advice would be appreciated. I am a beginner programmer.
from iexfinance import get_historical_data
import pandas as pd
import matplotlib.pyplot as plt
def tester():
start_date = '20170828'
end_date = '20180828'
symbols =['GOOG', 'IBM', 'CRON']
for symbol in symbols:
f_temp = get_historical_data(symbol, start_date, end_date, output_format='pandas')
df_close = pd.DataFrame(f_temp['close'])
df_open = pd.DataFrame(f_temp['open'])
df_date_string =
pd.to_datetime(f_temp.index).strftime("%Y%m%d").astype(str)
df = pd.merge(df_open, df_close, on=df_date_string)
df.columns = ['date', 'open', 'close']
plt.legend(symbols)
plot_data(df)
plt.show()
return df
def normalize_data(df):
return df/df.ix[0, :]
def plot_data(df):
normalized = normalize_data(df['close'])
plt.plot(df['date'], normalized)
plt.title("Normalized close stock prices")
plt.xlabel("Dates")
plt.ylabel("Close prices")
plt.tight_layout()
if __name__ == "__main__":
df = tester()
