Plotting candlestick data from a dataframe in Python

Question

I would like create a daily candlestick plot from data i downloaded from yahoo using pandas. I'm having trouble figuring out how to use the candlestick matplotlib function in this context. Here is the code:

#The following example, downloads stock data from Yahoo and plots it.
from pandas.io.data import get_data_yahoo
import matplotlib.pyplot as plt

from matplotlib.pyplot import subplots, draw
from matplotlib.finance import candlestick

symbol = "GOOG"

data = get_data_yahoo(symbol, start = '2013-9-01', end = '2013-10-23')[['Open','Close','High','Low','Volume']]

ax = subplots()

candlestick(ax,data['Open'],data['High'],data['Low'],data['Close'])

Thanks

Andrew.

score 8 · Answer 1 · edited Nov 23 '19 at 03:03

Using bokeh:

import io
from math import pi
import pandas as pd
from bokeh.plotting import figure, show, output_file

df = pd.read_csv(
    io.BytesIO(
        b'''Date,Open,High,Low,Close
2016-06-01,69.6,70.2,69.44,69.76
2016-06-02,70.0,70.15,69.45,69.54
2016-06-03,69.51,70.48,68.62,68.91
2016-06-04,69.51,70.48,68.62,68.91
2016-06-05,69.51,70.48,68.62,68.91
2016-06-06,70.49,71.44,69.84,70.11
2016-06-07,70.11,70.11,68.0,68.35'''
    )
)

df["Date"] = pd.to_datetime(df["Date"])

inc = df.Close > df.Open
dec = df.Open > df.Close
w = 12*60*60*1000

TOOLS = "pan,wheel_zoom,box_zoom,reset,save"

p = figure(x_axis_type="datetime", tools=TOOLS, plot_width=1000, title
= "Candlestick")
p.xaxis.major_label_orientation = pi/4
p.grid.grid_line_alpha=0.3

p.segment(df.Date, df.High, df.Date, df.Low, color="black")
p.vbar(df.Date[inc], w, df.Open[inc], df.Close[inc], fill_color="#D5E1DD", line_color="black")
p.vbar(df.Date[dec], w, df.Open[dec], df.Close[dec], fill_color="#F2583E", line_color="black")

output_file("candlestick.html", title="candlestick.py example")

show(p)

Code above forked from here: http://docs.bokeh.org/en/latest/docs/gallery/candlestick.html

score 5 · Answer 2 · answered Jun 15 '15 at 11:48

I have no reputation to comment @randall-goodwin answer, but for pandas 0.16.2 line:

# convert the datetime64 column in the dataframe to 'float days'
data.Date = mdates.date2num(data.Date)

must be:

data.Date = mdates.date2num(data.Date.dt.to_pydatetime())

because matplotlib does not support the numpy datetime64 dtype

score 3 · Answer 3 · answered Jul 30 '14 at 18:46

I stumbled across a great pastebin entry: http://pastebin.com/ne7Fjdiq that does this well. I too was having trouble getting the calling syntax right. It usually revolves around transforming your data in simple ways to get the function to work right. My issue was with the datetime. There must be something in my format data. Once I replaced the Date series with range(maxdata) then it worked.

data = pandas.read_csv('data.csv', parse_dates={'Timestamp': ['Date', 'Time']}, index_col='Timestamp')
ticks = data.ix[:, ['Price', 'Volume']]
bars = ticks.Price.resample('1min', how='ohlc')
barsa = bars.fillna(method='ffill')
fig = plt.figure()
fig.subplots_adjust(bottom=0.1)
ax = fig.add_subplot(111)
plt.title("Candlestick chart")
volume = ticks.Volume.resample('1min', how='sum')
value = ticks.prod(axis=1).resample('1min', how='sum')
vwap = value / volume
Date = range(len(barsa))
#Date = matplotlib.dates.date2num(barsa.index)#
DOCHLV = zip(Date , barsa.open, barsa.close, barsa.high, barsa.low, volume)
matplotlib.finance.candlestick(ax, DOCHLV, width=0.6, colorup='g', colordown='r', alpha=1.0)
plt.show()

score 2 · Answer 4 · answered Jul 26 '16 at 04:24

Here is the solution:

from pandas.io.data import get_data_yahoo
import matplotlib.pyplot as plt
from matplotlib import dates as mdates
from matplotlib import ticker as mticker
from matplotlib.finance import candlestick_ohlc
import datetime as dt
symbol = "GOOG"

data = get_data_yahoo(symbol, start = '2014-9-01', end = '2015-10-23')
data.reset_index(inplace=True)
data['Date']=mdates.date2num(data['Date'].astype(dt.date))
fig = plt.figure()
ax1 = plt.subplot2grid((1,1),(0,0))
plt.ylabel('Price')
ax1.xaxis.set_major_locator(mticker.MaxNLocator(6))
ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))

candlestick_ohlc(ax1,data.values,width=0.2)

score 1 · Answer 5 · edited May 23 '17 at 12:25

Found this question when I too was looking how to use candlestick with a pandas dataframe returned from one of the DataReader services like get_data_yahoo. I eventually figured it out. One of the keys was this other question, answered by Wes McKinney and RJRyV. Here is that link:

Pandas convert dataframe to array of tuples

The key was to read the candlestick.py function definition to determine how it expected to receive the data. The date needed to be converted first, then the entire dataframe needed to be converted to an array of tuples.

Here is the final code that worked for me. Maybe there is some other Candlestick chart out there somewhere that works directly on a pandas dataframe returned from one of the stock quote services. That would be very nice.

# Imports
from pandas.io.data import get_data_yahoo
from datetime import datetime, timedelta
import matplotlib.dates as mdates
from matplotlib.pyplot import subplots, draw
from matplotlib.finance import candlestick
import matplotlib.pyplot as plt

# get the data on a symbol (gets last 1 year)
symbol = "TSLA"
data = get_data_yahoo(symbol, datetime.now() - timedelta(days=365))

# drop the date index from the dateframe
data.reset_index(inplace = True)

# convert the datetime64 column in the dataframe to 'float days'
data.Date = mdates.date2num(data.Date)

# make an array of tuples in the specific order needed
dataAr = [tuple(x) for x in data[['Date', 'Open', 'Close', 'High', 'Low']].to_records(index=False)]

# construct and show the plot
fig = plt.figure()
ax1 = plt.subplot(1,1,1)
candlestick(ax1, dataAr)
plt.show()

Plotting candlestick data from a dataframe in Python

5 Answers5