CODEWITHSUNDEEP
pythonpython-3.xmatplotlibplotly
Jaffer Wilson
Jaffer Wilson

Reputation: 7273

Plotting color array using matplotlib or plotly Python3

I am trying to plot the candles using the OHLC values. But I am now willing to plot only the color of the candles.
I am trying to predict the close price and plotting it using the matplotlib. See the following: 

plt.figure(figsize=(21,7))
plt.plot(yTest,label='Price',color='blue')
plt.plot(test_pred_list,label='Predicted',color='red')
plt.title('Price vs Predicted')
plt.legend(loc='upper left')
plt.show()

output image

What I am willing to achieve is the graph plotted like a box of same size, and the color of the box should resemble the color of the candle in the test and predicted. See the example image of what I am willing to achieve:
test output

The above output consists of only the color of the candles that is decided by checking the open and close values.

Here is the sample data. The Real dataset and the Predicted values of the Close price.

Edited
Please suggest me the above is unachievable then can the below is possible with such dataset.
output achieveable or not

Upvotes: 0

Views: 442

Answers (1)

Ed Smith
Ed Smith

Reputation: 13216

So, if I understand, you really just want to draw a series of rectangles. This can be done by adding patches in matplotlib coloured by open > close,

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D
from matplotlib.patches import Rectangle

def draw_rects(ax, quotes, width=5., height=1., yloc=1., colorup='g', 
               colordown='r', edgecolor='k', alpha=1.0):

    OFFSET = width / 2.0
    patches = []
    for q in quotes:
        t, open, close, high, low = q[:5]
        if close > open:
            color = colorup
        else:
            color = colordown

        rect = Rectangle(
            xy=(t - OFFSET, yloc),
            width=width,
            height=height,
            facecolor=color,
            edgecolor=edgecolor,
        )
        rect.set_alpha(alpha)
        patches.append(rect)
        ax.add_patch(rect)

    ax.autoscale_view()

    return patches

fig, ax = plt.subplots(1,1)
quotes = np.genfromtxt("./out.csv", skip_header=1, delimiter=',')
p1 = draw_rects(ax, quotes, yloc=1)
p2 = draw_rects(ax, quotes, yloc=4)
labels = [item.get_text() for item in ax.get_yticklabels()]
labels[2] = 'Predicted'
labels[8] = 'Real'
ax.set_yticklabels(labels)
plt.show()

which looks like this,

enter image description here

you can adjust width, edgecolor, etc as needed. I've plotted the real data for both as the predicted link you had is not formatted in the same way. I've added the same data at a different yloc to draw_rects and changed the y tick labels as an example.

The data in out.csv is just

time,open,high,low,close
10,1.1661,1.16615,1.16601,1.16603
20,1.16623,1.16623,1.1661,1.1661
30,1.16617,1.16624,1.16617,1.16623
40,1.16613,1.16618,1.16612,1.16618
50,1.16615,1.16615,1.16612,1.16613
60,1.16613,1.16615,1.16613,1.16615
70,1.16617,1.16621,1.16612,1.16612
80,1.16618,1.16626,1.16615,1.16617
90,1.16614,1.16619,1.16614,1.16618
100,1.16618,1.16618,1.16609,1.16614

Upvotes: 1

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