Simple way to get data from yahoo finance

Hi guys,
If you are passionate stock market trader, and love to have your own japanese candlestick chart for technical analysis, and not know how to do this. I will show you most comon way, in a few simple steps. This  example show you how to get "Google" stock data from yahoo finance.  Code is written in Python .

So, let's get started  

The first file : "yahoo_finance_data.py",  allows you to get financial data from yahoo for preferred stock , and store them in one csv file.

Code:


# import matplotlib.pyplot as plt
# from matplotlib import style
import pandas as pd
import datetime as dt    
import pandas_datareader.data as pdtr      

#style.use('ggplot')

start_date = dt.datetime(2010, 1, 1)
end_date =  dt.datetime.now()

df = pdtr.DataReader('GOOG', 'yahoo', start_date, end_date)
#print(df)
#print(df.head())
#print(df.tail())

df.to_csv('goog.csv')



Now when we have information about Google price movement for the desired time interval, we need to switch them to the chart. Make new python  file : " plot_linear_data.py " , and write this code below.

Code:



import matplotlib.pyplot as plt
from matplotlib import style
import pandas as pd
import datetime as dt
import pandas_datareader.data as pdtr


style.use('ggplot')

df = pd.read_csv('goog.csv', parse_dates=True, index_col=0)
#print(df.head())
# print(df[['Open', 'High']])
# df['Adj Close'].plot()
# plt.show()

df['100ma'] = df['Adj Close'].rolling(window=100, min_periods=0).mean()
df.dropna(inplace=True)

print(df.head())

ax1 = plt.subplot2grid((6, 1), (0, 0), rowspan=5, colspan=1)
ax2 = plt.subplot2grid((6, 1), (5, 0), rowspan=1, colspan=1, sharex=ax1)

ax1.plot(df.index, df['Adj Close'])
ax1.plot(df.index, df['100ma'])
ax2.bar(df.index, df['Volume'])

plt.show()



and  result is a nice linear chart:
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Next step is candlestick chart. So , make new python file:" candlestick_graf.py ",  and copy/paste code below.

Code:


import matplotlib.pyplot as plt
from matplotlib import style
from mpl_finance import candlestick_ohlc
import matplotlib.dates as mdates
import pandas as pd
import datetime as dt
import pandas_datareader.data as pdtr


style.use('ggplot')

df = pd.read_csv('goog.csv', parse_dates=True, index_col=0)

# df['100ma'] = df['Adj Close'].rolling(window=100, min_periods=0).mean()

df_ohlc = df['Adj Close'].resample('10D').ohlc()
df_volume = df['Volume'].resample('10D').sum()

df_ohlc.reset_index(inplace=True)

df_ohlc['Date'] = df_ohlc['Date'].map(mdates.date2num)

ax1 = plt.subplot2grid((6, 1), (0, 0), rowspan=5, colspan=1)
ax2 = plt.subplot2grid((6, 1), (5, 0), rowspan=1, colspan=1, sharex=ax1)
ax1.xaxis_date()

candlestick_ohlc(ax1, df_ohlc.values, width=2, colorup='g')
ax2.fill_between(df_volume.index.map(mdates.date2num), df_volume.values, 0)

plt.show()



And vuala we have nice candlestick graph in the range of ten days per each candle.

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