Matplotlib data visualization three minutes entry, half an hour enchanted?

One , First of all, of course, the configuration environment

stay Windows Of DOM Enter the following command in the window （ stay pycharm Below Terminal Chung Tung ）

pip install -i https://pypi.tuna.tsinghua.edu.cn/simple matplotlib

（ notes ： If Xiaobian remembers correctly , This bag has more than fifty M, If you do not add domestic image source , It will continue to download for several hours ...）

Two ,3 Minute quick start

1, The import module

import matplotlib.pyplot as plt  #  Import matplotlib modular 
#  Import numpy and pandas modular , You may use 
import numpy as np
import pandas as pd

2, Several common function images （y=x, y=x^2 +3, y=sin(x)）

① y=x Images

x = np.linspace(-10, 10, 10)  #  Set up y=x Of x Axis 

# plt.plot（） It means drawing a line chart , first x Express x Value on axis , the second x Express y Value on axis （ because y=x Of x Axis and y It's like a shaft ）,
# marker Represents the mark shape corresponding to each selected point  , color='r' Indicates that the line color is red Red , linestyle='--'  Represents a broken line 
#  The line style of is '--', linewidth Indicates the line width of the polyline , label The label text that represents the content of the marked graphic 
plt.plot(x, x, marker='o', color='r', linestyle='--', linewidth=1, label='y=x')
plt.legend()
plt.show()  #  Show pictures 

notes ： Code shorthand

plt.plot(x, x, marker='o', color='r', linestyle='--', linewidth=1, label='y=x')

plt.plot(x, x, marker='o', c='r', ls='--', lw=1, label='y=x')  #  The effect same as above 

plt.plot(x, x, 'o--r', lw=1, label='y=x')  #  ditto , namely  marker,color,linestyle The parameters in can be mixed together , Don't distinguish the order ( But you can't put -- Two of them - Write separately )

notes ： About marker,color, linestyle There are many more parameters in , The contents in the help manual are as follows

**Markers**

=============   ===============================
character       description
=============   ===============================
``'.'``         point marker
``','``         pixel marker
``'o'``         circle marker
``'v'``         triangle_down marker
``'^'``         triangle_up marker
``'<'``         triangle_left marker
``'>'``         triangle_right marker
``'1'``         tri_down marker
``'2'``         tri_up marker
``'3'``         tri_left marker
``'4'``         tri_right marker
``'8'``         octagon marker
``'s'``         square marker
``'p'``         pentagon marker
``'P'``         plus (filled) marker
``'*'``         star marker
``'h'``         hexagon1 marker
``'H'``         hexagon2 marker
``'+'``         plus marker
``'x'``         x marker
``'X'``         x (filled) marker
``'D'``         diamond marker
``'d'``         thin_diamond marker
``'|'``         vline marker
``'_'``         hline marker
=============   ===============================

**Line Styles**

=============    ===============================
character        description
=============    ===============================
``'-'``          solid line style
``'--'``         dashed line style
``'-.'``         dash-dot line style
``':'``          dotted line style
=============    ===============================
**Colors**

The supported color abbreviations are the single letter codes

=============    ===============================
character        color
=============    ===============================
``'b'``          blue
``'g'``          green
``'r'``          red
``'c'``          cyan
``'m'``          magenta
``'y'``          yellow
``'k'``          black
``'w'``          white
=============    ===============================

② y=x^2 +3 Images

#  Solve the problem of Chinese garbled code 
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False

x = np.linspace(-10, 10, 100)  #  Set up x Shaft value 
y = x**2 + 3  #  Set up y Shaft value 

plt.plot(x, y, '--g', lw=1, label='y=x^2+3')
# size Indicates the title of the graphic content 
plt.title(' Broken line diagram ', c='r', size=15)
plt.legend()
plt.show()  #  Show pictures 

③ y=sin(x) Images

#  Solve the problem of Chinese garbled code 
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False

x = np.linspace(-10, 10, 100)
y = np.sin(x)

plt.plot(x, y, '--g', lw=1, label='y=sin(x)')
plt.title(' Broken line diagram ', c='r', size=15)
plt.legend()
plt.xlabel(' This is a x Axis ', c='b', size=13)  #  Set up x Label text for axis 
plt.ylabel(' This is a y Axis ', c='k', size=13)  #  Set up y Label text for axis 
plt.xlim(-2*np.pi, 2*np.pi)  #  Set up x Axis display range 
plt.ylim(-1, 1)  #  Set up y Axis display range 
plt.xticks(np.arange(-2*np.pi, 2*np.pi, np.pi/4), rotation=45)  #  Limit x Display density of axis ,rotation=45 Express x The scale font on the axis rotates 45°
plt.yticks(np.arange(-1, 1.1, 0.2))  #  Limit y Display density of axis 
plt.show()

④ take 3 A picture composes a picture

#  Solve the problem of Chinese garbled code 
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False

x = np.linspace(-5, 5, 100)
y1 = x
y2 = x**2 + 3
y3 = np.sin(x)

plt.figure(figsize=(9, 6))  #  Set canvas size ,9  namely 900px,6  namely 600px（ Don't set it too big ）
plt.plot(x, y1, ':b', lw=2, label='y=x')
plt.plot(x, y2, '-r', lw=1, label='y=x^2+3')
plt.plot(x, y3, '--g', lw=1.5, label='y=sin(x)')
plt.title(' Broken line diagram ', c='r', size=15)
plt.legend()
plt.xlabel(' This is a x Axis ', c='b', size=13)
plt.ylabel(' This is a y Axis ', c='k', size=13)
plt.show()

⑤ Draw multiple pictures on one canvas

#  Solve the problem of Chinese garbled code 
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False

x = np.linspace(-5, 5, 100)
y1 = x
y2 = x**2 + 3
y3 = np.sin(x)
y4 = np.cos(x)

pf = plt.figure(figsize=(10, 7))
as1 = pf.add_subplot(2, 2, 1)  #  Indicates that the drawing is divided into 2 That's ok 2 Column ,as1 In the 1 A place 
as2 = pf.add_subplot(2, 2, 2)  #  Indicates that the drawing is divided into 2 That's ok 2 Column ,as2 In the 2 A place 
as3 = pf.add_subplot(2, 2, 3)  #  Indicates that the drawing is divided into 2 That's ok 2 Column ,as3 In the 3 A place 
as4 = pf.add_subplot(2, 2, 4)  #  Indicates that the drawing is divided into 2 That's ok 2 Column ,as4 In the 4 A place 
as1.plot(x, y1, ':b', lw=2, label='y=x')
as2.plot(x, y2, '-r', lw=1, label='y=x^2+3')
as3.plot(x, y3, '--g', lw=1.5, label='y=sin(x)')
as4.plot(x, y4, '-.k', lw=1.5, label='y=cos(x)')
as1.legend()
as2.legend()
as3.legend()
as4.legend()
plt.show()

3、 ... and , Draw a histogram

#  Solve the problem of Chinese garbled code 
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False

x = np.arange(1, 13)
y = np.random.randint(1, 50, 12)
lab = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l']

plt.figure(figsize=(9, 6.5))
plt.bar(x, y, color='b', tick_label=lab, label=' Bar charts ')
plt.xticks(np.arange(1, 13))
plt.title(' Column chart exercise ', color='b', size=13)
plt.legend()
plt.xlabel(' Case number ')
plt.ylabel(' Box size ')
plt.show()

Four , Draw a pie chart

#  Solve the problem of Chinese garbled code 
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False

kinds = [' Siberian Husky ', ' Alaska ', ' Samoye ', ' Yellow lion king ']
num = [0.3, 0.1, 0.2, 0.4]

plt.figure(figsize=(9, 6.5))  # plt.figure  It means drawing a pie chart 
# explode=[0, 0, 0.1, 0]  Highlight 
plt.pie(num, labels=kinds, autopct='%.2f%%', explode=[0, 0, 0.1, 0])
plt.show()

5、 ... and , A profound

1, Crawl data

Climb the price of vegetables in a wholesale market for nearly a year

import requests
from lxml import etree
import csv
from concurrent.futures import ThreadPoolExecutor
import time

f = open("vegetables.csv", mode="w", newline='', encoding="utf-8")
csv_write = csv.writer(f)


def down_one_page(url):
    res = requests.get(url=url, headers=headers).text
    # print(res)
    html = etree.HTML(res)
    table = html.xpath('/html/body/div[2]/div[4]/div[1]/table')[0]
    # print(table)
    # trs = table.xpath('./tr')[1:]
    trs = table.xpath('./tr[position()>1]')
    # print(len(trs))
    for tr in trs:
        txt = tr.xpath('./td/text()')
        #  Get rid of \\ /
        txt = (item.replace("\\", "").replace("/", "") for item in txt)
        # print(list(txt))
        csv_write.writerow(list(txt))
        # print(list(txt))
    new_name = url.split("/")[-1].split(".")[0]
    print(" The first  \033[31;1m%s\033[0m  Page download complete ！！！" % new_name)


if __name__ == '__main__':
    headers = {
    
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/89.0.4389.90 Safari/537.36 Edg/89.0.774.54"
    }

    # for i in range(1, 14870):
    # down_one_page("http://www.xinfadi.com.cn/marketanalysis/0/list/%s.shtml" % i)

    user_input = int(input("Total 15069 pages,please input a page number>>>:"))
    start_time = time.time()
    with ThreadPoolExecutor(32) as t:
        for i in range(1, user_input + 1):
            t.submit(down_one_page, "http://www.xinfadi.com.cn/marketanalysis/0/list/%s.shtml" % i)

    print("Download over,it takes \033[31;1m%s\033[0m seconds" % (time.time() - start_time))

about 10 Ten thousand data ！

2, Simple processing of data

First read the first few lines to see the data

import pandas as pd

output_file = 'vage.csv'
vege_data = pd.read_csv('vegetables.csv', header=None)
print(vege_data.head(5))

     0     1     2     3    4  5           6
0   Samito   20.0  22.5  25.0   Cherries    Jin   2021-05-15
1   Sheep's brain   42.0  42.5  43.0   Mutton    Jin   2021-05-15
2   Sheep bone   11.0  11.5  12.0   Mutton    Jin   2021-05-15
3    Lamb belly   32.0  32.0  32.0   Mutton    Jin   2021-05-15
4   Lamb fillet   42.0  42.0  42.0   Mutton    Jin   2021-05-15

For the convenience of drawing in the back , Sort the time column

import pandas as pd

output_file = 'vage.csv'
vege_data = pd.read_csv('vegetables.csv', header=None, index_col=6).sort_index()
print(vege_data.head(5))

               0    1     2    3    4  5
6                                       
2020-05-13     Thread eggplant   1.0  1.50  2.0  | Yue Yun    Jin 
2020-05-13     Chrysanthemum   1.2  1.60  2.0     liao    Jin 
2020-05-13    Lettuce   1.2  1.50  1.8     liao    Jin 
2020-05-13     Water chestnut   1.8  1.90  2.0     Wan    Jin 
2020-05-13   Golden pumpkin   0.9  1.05  1.2   Joan cantaloupe    Jin 

select ‘ Whole cattle ’ All the corresponding lines

import pandas as pd

output_file = 'vage.csv'
vege_data = pd.read_csv('vegetables.csv', header=None, index_col=6).sort_index()
new_data = vege_data[vege_data[0] == ' Whole cattle ']
print(new_data)

             0      1      2      3    4  5
6                                          
2020-05-15   Whole cattle   30.00  30.50  31.00    Ordinary    Jin 
2020-05-16   Whole cattle   30.00  30.50  31.00    Ordinary    Jin 
2020-05-17   Whole cattle   30.00  30.50  31.00    Ordinary    Jin 
2020-05-18   Whole cattle   30.50  30.75  31.00    Ordinary    Jin 
2020-05-19   Whole cattle   30.50  30.75  31.00    Ordinary    Jin 
...         ..    ...    ...    ...  ... ..
2021-05-12   Whole cattle   34.00  34.00  34.00   Beef    Jin 
2021-05-13   Whole cattle   34.00  34.00  34.00   Beef    Jin 
2021-05-14   Whole cattle   34.25  34.25  34.25   Beef    Jin 
2021-05-15   Whole cattle   34.25  34.25  34.25   Beef    Jin 
2021-05-16   Whole cattle   34.25  34.25  34.25   Beef    Jin 

[250 rows x 6 columns]

It is found that there is a year's data , only 250 That's ok , Save it before you look

import pandas as pd

output_file = 'vage.csv'
vege_data = pd.read_csv('vegetables.csv', header=None, index_col=6).sort_index()
# print(vege_data.head(5))
new_data = vege_data[vege_data[0] == ' Whole cattle ']
# print(new_data)
new_data.to_csv(output_file, header=False, encoding='utf-8')

During observation, I found that there was no price for a period of time

So take 2020-09-30 Data after this time period

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

data = pd.read_csv('vage.csv', header=None)[29:]
print(data)

              0   1      2      3      4    5  6
29   2020-09-30   Whole cattle   34.00  34.00  34.00    Ordinary    Jin 
30   2020-10-01   Whole cattle   34.00  34.00  34.00    Ordinary    Jin 
31   2020-10-02   Whole cattle   33.00  33.50  34.00    Ordinary    Jin 
32   2020-10-03   Whole cattle   33.00  33.50  34.00    Ordinary    Jin 
33   2020-10-04   Whole cattle   33.00  33.50  34.00    Ordinary    Jin 
..          ...  ..    ...    ...    ...  ... ..
245  2021-05-12   Whole cattle   34.00  34.00  34.00   Beef    Jin 
246  2021-05-13   Whole cattle   34.00  34.00  34.00   Beef    Jin 
247  2021-05-14   Whole cattle   34.25  34.25  34.25   Beef    Jin 
248  2021-05-15   Whole cattle   34.25  34.25  34.25   Beef    Jin 
249  2021-05-16   Whole cattle   34.25  34.25  34.25   Beef    Jin 

[221 rows x 7 columns]

Process finished with exit code 0

3, Yes ‘ Whole cattle ’ Draw a line chart of prices

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

data = pd.read_csv('vage.csv', header=None)[29:]
# print(data)

#  Solve the problem of Chinese garbled code 
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False

x = data[0]
y = data[3]

plt.figure(figsize=(12, 8))
plt.plot(x, y, '-r', lw=2, label=' Price ')
plt.legend()
plt.xlabel(' Time / God ', c='b', size=13)
plt.ylabel(' The unit price / element ', c='b', size=13)
plt.title(' Line chart of whole cow price ', c='g', size=20)
plt.ylim(32, 36)
plt.xticks(np.arange(0, 220, 8), rotation=45)
plt.show()