import numpy as np

from numpy.random import randn

import matplotlib.pyplot as plt

from matplotlib.font_manager import FontProperties

font = FontProperties(fname=r'c:\windows\fonts\simsun.ttc')

# 修改背景为条纹

plt.style.use('ggplot')

x = np.arange(1, 20, 1)

print(x)

# [ 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19]

# 拟合一条水平散点线

np.random.seed(1)

y_linear = x + 10 * np.random.randn(19)

# print(y_linear)

# [ 17.24345364  -4.11756414  -2.28171752  -6.72968622  13.65407629

#  -17.01538697  24.44811764   0.38793099  12.19039096   7.50629625

#   25.62107937  -8.60140709   9.77582796  10.15945645  26.33769442

#    5.00108733  15.27571792   9.22141582  19.42213747]

# 拟合一条x²的散点线

y_quad = x**2 + 10 * np.random.randn(19)

print(y_quad)

# [  6.82815214  -7.00619177  20.4472371   25.01590721  30.02494339

#   45.00855949  42.16272141  62.77109774  71.64230566  97.3211192

#  126.30355467 137.08339248 165.03246473 189.128273   216.54794359

#  249.28753869 288.87335401 312.82689651 363.34415698]

# s是散点大小

fig = plt.figure()

ax1 = fig.add_subplot(121)

plt.scatter(x, y_linear, s=30, color='r', label='蓝点')

plt.scatter(x, y_quad, s=100, color='b', label='红点')

ax2 = fig.add_subplot(122)

plt.plot(x, y_linear, color='r')

plt.plot(x, y_quad, color='b')

# 限制x轴和y轴的范围取值

plt.xlim(min(x) - 1, max(x) + 1)

plt.ylim(min(y_quad) - 10, max(y_quad) + 10)

fig.suptitle('散点图+直线图', fontproperties=font, fontsize=20)

ax1.set_title('散点图', fontproperties=font)

ax1.legend(prop=font)

ax2.set_title('直线图', fontproperties=font)

plt.show()

import numpy as np

import matplotlib.pyplot as plt

from pylab import mpl

from matplotlib.font_manager import FontProperties

font = FontProperties(fname=r'c:\windows\fonts\simsun.ttc')

mpl.rcParams['font.sans-serif'] = ['SimHei']

fig, ax = plt.subplots(subplot_kw=dict(aspect="equal"))

recipe = ['优', '良', '轻度污染', '中度污染', '重度污染', '严重污染', '缺']

data = [2, 49, 21, 9, 11, 6, 2]

colors = ['lime', 'yellow', 'darkorange', 'red', 'purple', 'maroon', 'grey']

wedges, texts, texts2 = ax.pie(data,

                               wedgeprops=dict(width=0.5),

                               startangle=40,

                               colors=colors,

                               autopct='%1.0f%%',

                               pctdistance=0.8)

plt.setp(texts2, size=14, weight="bold")

bbox_props = dict(boxstyle="square,pad=0.3", fc="w", ec="k", lw=0.72)

kw = dict(xycoords='data',

          textcoords='data',

          arrowprops=dict(arrowstyle="->"),

          bbox=None,

          zorder=0,

          va="center")

for i, p in enumerate(wedges):

    ang = (p.theta2 - p.theta1) / 2. + p.theta1

    y = np.sin(np.deg2rad(ang))

    x = np.cos(np.deg2rad(ang))

    horizontalalignment = {-1: "right", 1: "left"}[int(np.sign(x))]

    connectionstyle = "angle,angleA=0,angleB={}".format(ang)

    kw["arrowprops"].update({"connectionstyle": connectionstyle})

    ax.annotate(recipe[i],

                xy=(x, y),

                xytext=(1.25 * np.sign(x), 1.3 * y),

                size=16,

                horizontalalignment=horizontalalignment,

                fontproperties=font,

                **kw)

ax.set_title("饼图示例", fontproperties=font)

plt.show()

# plt.savefig('jiaopie2.png?x-oss-process=style/watermark')

import numpy as np

import matplotlib.pyplot as plt

import pandas as pd

from matplotlib.font_manager import FontProperties

font = FontProperties(fname=r'c:\windows\fonts\simsun.ttc')

df = pd.DataFrame(np.random.rand(10, 5), columns=['A', 'B', 'C', 'D', 'E'])

plt.figure(figsize=(10, 4))

# 创建图表、数据

f = df.boxplot(

    sym='o',  # 异常点形状，参考marker

    vert=True,  # 是否垂直

    whis=1.5,  # IQR，默认1.5，也可以设置区间比如[5,95]，代表强制上下边缘为数据95%和5%位置

    patch_artist=True,  # 上下四分位框内是否填充，True为填充

    meanline=False,

    showmeans=True,  # 是否有均值线及其形状

    showbox=True,  # 是否显示箱线

    showcaps=True,  # 是否显示边缘线

    showfliers=True,  # 是否显示异常值

    notch=False,  # 中间箱体是否缺口

    return_type='dict'  # 返回类型为字典

)

plt.title('boxplot')

for box in f['boxes']:

    box.set(color='b', linewidth=1)  # 箱体边框颜色

    box.set(facecolor='b', alpha=0.5)  # 箱体内部填充颜色

for whisker in f['whiskers']:

    whisker.set(color='k', linewidth=0.5, linestyle='-')

for cap in f['caps']:

    cap.set(color='gray', linewidth=2)

for median in f['medians']:

    median.set(color='DarkBlue', linewidth=2)

for flier in f['fliers']:

    flier.set(marker='o', color='y', alpha=0.5)

# boxes, 箱线

# medians, 中位值的横线,

# whiskers, 从box到error bar之间的竖线.

# fliers, 异常值

# caps, error bar横线

# means, 均值的横线

plt.show()

import pandas as pd

import matplotlib.pyplot as plt

from matplotlib.font_manager import FontProperties

font = FontProperties(fname=r'c:\windows\fonts\simsun.ttc')

header_list = ['方程组', '函数', '导数', '微积分', '线性代数', '概率论', '统计学']

py3_df = pd.read_excel('py3.xlsx', header=None,   skiprows=[0, 1], names=header_list)

# 处理带有NaN的行

py3_df = py3_df.dropna(axis=0) #<class 'pandas.core.frame.DataFrame'>

print(py3_df)

# 自定义映射

map_dict = {

    '不会': 0,

    '了解': 1,

    '熟悉': 2,

    '使用过': 3,

}

for header in header_list:

    py3_df[header] = py3_df[header].map(map_dict)

unable_series = (py3_df == 0).sum(axis=0)

know_series = (py3_df == 1).sum(axis=0)

familiar_series = (py3_df == 2).sum(axis=0)

use_series = (py3_df == 3).sum(axis=0)

unable_label = '不会'

know_label = '了解'

familiar_label = '熟悉'

use_label = '使用过'

for i in range(len(header_list)):

    bottom = 0

    # 描绘不会的条形图

    plt.bar(x=header_list[i], height=unable_series[i],  width=0.60, color='r', label=unable_label)

    if unable_series[i] != 0:

        plt.text(header_list[i], bottom, s=unable_series[i],   ha='center', va='bottom', fontsize=15, color='white')

    bottom += unable_series[i]

    # 描绘了解的条形图

    plt.bar(x=header_list[i], height=know_series[i],  width=0.60, color='y', bottom=bottom, label=know_label)

    if know_series[i] != 0:

        plt.text(header_list[i], bottom, s=know_series[i],  ha='center', va='bottom', fontsize=15, color='white')

    bottom += know_series[i]

    # 描绘熟悉的条形图

    plt.bar(x=header_list[i], height=familiar_series[i],    width=0.60, color='g', bottom=bottom, label=familiar_label)

    if familiar_series[i] != 0:

        plt.text(header_list[i], bottom, s=familiar_series[i], ha='center', va='bottom', fontsize=15, color='white')

    bottom += familiar_series[i]

    # 描绘使用过的条形图

    plt.bar(x=header_list[i], height=use_series[i],  width=0.60, color='b', bottom=bottom, label=use_label)

    if use_series[i] != 0:

        plt.text(header_list[i], bottom, s=use_series[i], ha='center', va='bottom', fontsize=15, color='white')

    unable_label = know_label = familiar_label = use_label = ''

plt.xticks(header_list, fontproperties=font)

plt.ylabel('人数', fontproperties=font)

plt.title('Python3期数学摸底可视化', fontproperties=font)

plt.legend(prop=font, loc='upper left')

plt.show()

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