I try to do first steps with pandas.
After a few successful steps I stuck with the following task: display data with OHLC bars.
I downloaded data for Apple stock from Google Finance and stored it to *.csv file.
After a lot of search I wrote the following code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import datetime as dt
from matplotlib.finance import candlestick_ohlc
#read stored data
#First two lines of csv:
#Date,Open,High,Low,Close
#2010-01-04,30.49,30.64,30.34,30.57
data = pd.read_csv("AAPL.csv")
#graph settings
fig, ax = plt.subplots()
ax.xaxis_date()
ax.xaxis.set_major_formatter(mdates.DateFormatter("%Y-%m-%d"))
plt.xlabel("Date")
plt.ylabel("Price")
plt.title("AAPL")
#convert date to float format
data['Date2'] = data['Date'].map(lambda d: mdates.date2num(dt.datetime.strptime(d, "%Y-%m-%d")))
candlestick_ohlc(ax, (data['Date2'], data['Open'], data['High'], data['Low'], data['Close']))
plt.show()
But it displays empty graph. What is wrong with this code?
Thanks.
You need to change the last line to combine tuples daily. The following code:
start = dt.datetime(2015, 7, 1)
data = pd.io.data.DataReader('AAPL', 'yahoo', start)
data = data.reset_index()
data['Date2'] = data['Date'].apply(lambda d: mdates.date2num(d.to_pydatetime()))
tuples = [tuple(x) for x in data[['Date2','Open','High','Low','Close']].values]
fig, ax = plt.subplots()
ax.xaxis_date()
ax.xaxis.set_major_formatter(mdates.DateFormatter("%Y-%m-%d"))
plt.xticks(rotation=45)
plt.xlabel("Date")
plt.ylabel("Price")
plt.title("AAPL")
candlestick_ohlc(ax, tuples, width=.6, colorup='g', alpha =.4);
Produces the below plot:
which you can further tinker with.
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