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# 0、通用代码
import pandas as pd
from numpy import arange
import matplotlib.pyplot as plt

reviews = pd.read_csv("fandango_scores.csv")
num_cols = ["RT_user_norm","Metacritic_user_nom","IMDB_norm","Fandango_Ratingvalue","Fandango_Stars"]
norm_reviews = reviews[num_cols]
print (norm_reviews[:1])

## 设置中文乱码问题
from pylab import mpl
mpl.rcParams['font.sans-serif'] = ['SimHei']

# 1、绘制简单柱状图
bar_heights = norm_reviews.ix[0,num_cols].values      ## 每个柱的高度
bar_positions = arange(5) + 0.75                      ## 每个柱离 0 值的距离
fig,ax= plt.subplots()                                ## 把图拿出来  ax 通常用来画图 fig 通常用来设置图
ax.bar(bar_positions,bar_heights,0.5)                 # ax.bar( 离0点横坐标 , 柱高度 , 柱宽度)
plt.show()

# 2、绘制带有title和label的柱状图
bar_heights = norm_reviews.ix[0,num_cols].values      ## 每个柱的高度
bar_positions = arange(5) + 0.75
tick_positions = range(1,6)
fig,ax = plt.subplots()

ax.bar(bar_positions, bar_heights, 0.5)               # ax.bar() 绘制纵向柱状图
ax.set_xticks(tick_positions)                         # 设置 x 轴刻度值
ax.set_xticklabels(num_cols,rotation=45)              # 设置 x 轴刻度值的旋转角度
ax.set_xlabel("Rating Source")                     # 设置 x 轴名称
ax.set_ylabel("Average Rating")                    # 设置 y 轴名称
ax.set_title("这是标题")                             # 设置 图表 标题
plt.show()

# 3、绘制横向柱状图
bar_heights = norm_reviews.ix[0,num_cols].values      ## 每个柱的高度
bar_positions = arange(5) + 0.75
tick_positions = range(1,6)
fig,ax = plt.subplots()

ax.barh(bar_positions, bar_heights, 0.5)               # ax.bar() 绘制横向柱状图
ax.set_xticks(tick_positions)                         # 设置 x 轴刻度值
ax.set_xticklabels(num_cols,rotation=45)              # 设置 x 轴刻度值的旋转角度
ax.set_xlabel("Rating Source")                     # 设置 x 轴名称
ax.set_ylabel("Average Rating")                    # 设置 y 轴名称
ax.set_title("这是标题")                             # 设置 图表 标题
plt.show()

# 4、绘制简单散点图
fig,ax = plt.subplots()
ax.scatter(norm_reviews["Fandango_Ratingvalue"], norm_reviews["RT_user_norm"])
ax.set_xlabel("Fandango")
ax.set_ylabel("Rotten Tomatoes")
plt.show()

# 5、绘制含有子图的散点图
fig = plt.figure(figsize = (5,10))
ax1 = fig.add_subplot(2,1,1)
ax2 = fig.add_subplot(2,1,2)
ax1.scatter(norm_reviews["Fandango_Ratingvalue"],norm_reviews["RT_user_norm"])
ax1.set_xlabel("Fandango")
ax1.seet_ylabel("Rotten Tomatoes")
ax2.scatter(norm_reviews["RT_user_norm"],norm_reviews["Fandango_Ratingvalue"])
ax2.set_xlabel("Rotten Tomatoes")
ax2.seet_ylabel("Fandango")
plt.show()

# 6、绘制简单区间柱形图( 添加 bins )
## 整理数据
fandango_distibution = norm_reviews["Fandango_Ratingvalue"].value_counts()
fandango_distibution = fandango_distibution.sort_index()
imdb_distribution = norm_reviews["IMDB_norm"].value_counts()
imdb_distribution = imdb_distribution.sort_index()
## 绘制图形
fig, ax = plt.subplots()
ax.hist(norm_reviews["Fandango_Ratingvalue"])
# ax.hist(norm_reviews["Fandango_Ratingvalue"],bins=20)      # 指定 Bins 划分格子数量
# ax.hist(norm_reviews["Fandango_Ratingvalue"],range=(4, 5),bins=20)  # range(x, y) 取x开始，y结束数据
plt.show()

# 7、绘制复杂的区间柱状图
fig = plt.figure(figsize=(5,20))
ax1 = fig.add_subplot(4,1,1)
ax2 = fig.add_subplot(4,1,2)
ax3 = fig.add_subplot(4,1,3)
ax4 = fig.add_subplot(4,1,4)
ax1.hist(norm_reviews["Fandango_Ratingvalue"],bins = 20, range=(0, 5))
ax1.set_title("Distribution of Fandango Ratings")
ax1.set_ylim(0,50)    # ax.set_ylim(x, y)  设置y轴坐标区间 x开始 y结束

ax2.hist(norm_reviews["RT_user_norm"],bins = 20, range=(0, 5))
ax2.set_title("Distribution of Rotten Tomatoes Ratings")
ax2.set_ylim(0,50)

ax3.hist(norm_reviews["Metacritic_user_nom"],bins = 20, range=(0, 5))
ax3.set_title("Distribution of Metacritic Ratings")
ax3.set_ylim(0,50)

ax4.hist(norm_reviews["IMDB_norm"],bins = 20, range=(0, 5))
ax4.set_title("Distribution of IMDB Ratings")
ax4.set_ylim(0,50)

plt.show()

# 8、单数据盒图( 四分图 )
fig, ax = plt.subplots()
ax.boxplot(norm_reviews["RT_user_norm"])  # ax.boxplot( )用来绘制盒图
ax.set_xticklabels(["Rotten Tomatoes"])
ax.tick_params(bottom="off", top="off", left="off", right="off")
ax.set_ylim(0, 5)
plt.show()

# 9、多数据盒图( 四分图 )
num_cols = ["RT_user_norm","Metacritic_user_nom","IMDB_norm","Fandango_Ratingvalue"]
fig, ax = plt.subplots()
ax.boxplot(norm_reviews[num_cols].values,c=line1_color)  # ax.boxplot( )用来绘制盒图
ax.set_xticklabels(num_cols,rotation=90)
ax.tick_params(bottom="off", top="off", left="off", right="off")    # 去除对应位置的刻度线
ax.set_ylim(0, 5)
plt.show()

# 10、设置折线等的颜色
line1_color = (0/255,107/255,164,255)
plt.plot(subset["MONTH"],subset["VALUE"],c=line1_color,label=labels)