Filling of graphic colors and lines in Matplotlib-Python Tutorial-php.cn

Filling of graphic colors and lines in Matplotlib

爱喝马黛茶的安东尼

Release： 2019-06-04 16:31:40

forward

4490 people have browsed it

Matplotlib is a Python 2D plotting library that can generate publication-quality graphics in a variety of hardcopy formats and interactive environments on a variety of platforms.

Filling of graphic colors and lines in Matplotlib

In the previous Matplotlib data visualization tutorial, we will introducehow to create stacked charts and pie charts. What I bring to you today is the filling of graphic colors and lines.

Color

The first change we want to make is to change plt.title to stock variable.

plt.title(stock)

Copy after login

Now, let’s introduce how to change the label color. We can do this by modifying our axis object:

ax1.xaxis.label.set_color(&#39;c&#39;)
ax1.yaxis.label.set_color(&#39;r&#39;)

Copy after login

If we run this, we'll see that the labels change color, just like in the words.

Next, we can specify specific numbers for the axes to be displayed, rather than an automatic selection like this:

ax1.set_yticks([0,25,50,75])

Copy after login

Next, I want to introduce padding. What fill does is fill the color between the variable and a value of your choice. For example, we can do this:

ax1.fill_between(date, 0, closep)

Copy after login

So here, our code is:

import matplotlib.pyplot as plt
import numpy as np
import urllib
import datetime as dt
import matplotlib.dates as mdates

def bytespdate2num(fmt, encoding=&#39;utf-8&#39;):
    strconverter = mdates.strpdate2num(fmt)
    def bytesconverter(b):
        s = b.decode(encoding)
        return strconverter(s)
    return bytesconverter


def graph_data(stock):

    fig = plt.figure()
    ax1 = plt.subplot2grid((1,1), (0,0))

    stock_price_url = &#39;http://chartapi.finance.yahoo.com/instrument/1.0/&#39;+stock+&#39;/chartdata;type=quote;range=10y/csv&#39;
    source_code = urllib.request.urlopen(stock_price_url).read().decode()
    stock_data = []
    split_source = source_code.split(&#39;\n&#39;)
    for line in split_source:
        split_line = line.split(&#39;,&#39;)
        if len(split_line) == 6:
            if &#39;values&#39; not in line and &#39;labels&#39; not in line:
                stock_data.append(line)


    date, closep, highp, lowp, openp, volume = np.loadtxt(stock_data,
                                                          delimiter=&#39;,&#39;,
                                                          unpack=True,
                                                          converters={0: bytespdate2num(&#39;%Y%m%d&#39;)})

    ax1.fill_between(date, 0, closep)

    for label in ax1.xaxis.get_ticklabels():
        label.set_rotation(45)
    ax1.grid(True)#, color=&#39;g&#39;, linestyle=&#39;-&#39;, linewidth=5)
    ax1.xaxis.label.set_color(&#39;c&#39;)
    ax1.yaxis.label.set_color(&#39;r&#39;)
    ax1.set_yticks([0,25,50,75])

    plt.xlabel(&#39;Date&#39;)
    plt.ylabel(&#39;Price&#39;)
    plt.title(stock)
    plt.legend()
    plt.subplots_adjust(left=0.09, bottom=0.20, right=0.94, top=0.90, wspace=0.2, hspace=0)
    plt.show()


graph_data(&#39;EBAY&#39;)

Copy after login

The result is:

Filling of graphic colors and lines in Matplotlib

filled one The problem is, we might end up covering everything. We can solve it with transparency:

ax1.fill_between(date, 0, closep)

Copy after login

Now, let’s introduce conditional fill. Let's assume the starting position on the chart is where we start buying eBay. Here, if the price is below this price, we can pad up to the original price, and then if it exceeds the original price, we can pad down. We could do this:

ax1.fill_between(date, closep[0], closep)

Copy after login

would generate:

Filling of graphic colors and lines in Matplotlib

If we wanted to show the gains/losses with red and green fills compared to the original price , green filling is used for rising (note: the color of foreign stock markets is opposite to domestic), red filling is used for falling? no problem! We can add a where parameter like this:

ax1.fill_between(date, closep, closep[0],where=(closep > closep[0]), facecolor=&#39;g&#39;, alpha=0.5)

Copy after login

Here, we fill the area between the current price and the original price, where the current price is higher than the original price. We give it a green foreground color because this is a rise, and we use a slight transparency.

Lines

We still can't apply labels to polygonal data (like fills), but we can implement empty lines as before, so we can:

ax1.plot([],[],linewidth=5, label='loss', color='r',alpha=0.5)
ax1.plot([],[],linewidth=5, label='gain', color='g',alpha=0.5)
ax1.fill_between(date, closep, closep[0],where=(closep > closep[0]), facecolor=&#39;g&#39;, alpha=0.5)
ax1.fill_between(date, closep, closep[0],where=(closep < closep[0]), facecolor='r', alpha=0.5)

Copy after login

This gives us some padding, as well as empty lines for handling labels, which we intend to display in the legend. The complete code here is:

import matplotlib.pyplot as plt
import numpy as npimport urllib
import datetime as dt
import matplotlib.dates as mdates

def bytespdate2num(fmt, encoding='utf-8'):
    strconverter = mdates.strpdate2num(fmt)    
    def bytesconverter(b):
        s = b.decode(encoding)        
        return strconverter(s)    
    
    return bytesconverter
def graph_data(stock):
    
    fig = plt.figure()
    ax1 = plt.subplot2grid((1,1), (0,0))
    
    stock_price_url = 'http://chartapi.finance.yahoo.com/instrument/1.0/'+stock+'/chartdata;type=quote;range=10y/csv'
    source_code = urllib.request.urlopen(stock_price_url).read().decode()
    stock_data = []
    split_source = source_code.split('\n')    
    for line in split_source:
        split_line = line.split(',')        
       if len(split_line) == 6:            
           if 'values' not in line and 'labels' not in line:
              stock_data.append(line)
    date, closep, highp, lowp, openp, volume = np.loadtxt(stock_data,
                                        delimiter=',',
                                        unpack=True,
                                        converters={0: bytespdate2num('%Y%m%d')})
    ax1.plot_date(date, closep,'-', label='Price')
    ax1.plot([],[],linewidth=5, label='loss', color='r',alpha=0.5)
    ax1.plot([],[],linewidth=5, label='gain', color='g',alpha=0.5)
    ax1.fill_between(date, closep, closep[0],where=(closep > closep[0]), facecolor=&#39;g&#39;, alpha=0.5)
    ax1.fill_between(date, closep, closep[0],where=(closep < closep[0]), facecolor='r', alpha=0.5)    
    for label in ax1.xaxis.get_ticklabels():
       label.set_rotation(45)
    ax1.grid(True)#, color='g', linestyle='-', linewidth=5)
    ax1.xaxis.label.set_color('c')
    ax1.yaxis.label.set_color('r')
    ax1.set_yticks([0,25,50,75])
    
    plt.xlabel('Date')
    plt.ylabel('Price')
    plt.title(stock)
    plt.legend()
    plt.subplots_adjust(left=0.09, bottom=0.20, right=0.94, top=0.90, wspace=0.2, hspace=0)
    plt.show()
graph_data('EBAY')

Copy after login

Now our result is:

Filling of graphic colors and lines in Matplotlib

The above is the detailed content of Filling of graphic colors and lines in Matplotlib. For more information, please follow other related articles on the PHP Chinese website!