import seaborn as sns
import numpy as np 
import matplotlib as mpl
from matplotlib import pyplot as plt 
import pandas as pd 
from datetime import datetime,timedelta
%matplotlib inline
plt.rcParams['font.sans-serif']=['SimHei'] # 用來正常顯示中文標簽
plt.rcParams['axes.unicode_minus']=False # 用來正常顯示負號
from datetime import datetime 

films=['穿過寒冬擁抱你','反貪風暴5：最終章','李茂扮太子','誤殺2','以年為單位的戀愛','黑客帝國：矩陣重啟','雄獅少年','魔法滿屋','汪汪隊立大功大電影','愛情神話']
regions=['中國','英國','澳大利亞','美國','美國','中國','英國','澳大利亞','美國','美國']
bos=['61,181','44,303','42,439','22,984','13,979','61,181','44,303','41,439','20,984','19,979']
persons=['31','23','56','17','9','31','23','56','17','9']
prices=['51','43','56','57','49','51','43','56','57','49']
showdate=['2022-12-03','2022-12-05','2022-12-01','2022-12-02','2022-11-05','2022-12-03','2022-12-05','2022-12-01','2022-12-02','2022-11-05']
ftypes=['劇情','動作','喜劇','劇情','劇情','愛情','動作','動畫','動畫','動畫']
points=['8.1','9.0','7.9','6.7','3.8','8.1','9.0','7.9','6.7','3.8']
filmdescript={
    'ftypes':ftypes,
    'bos':bos,
    'prices':prices,
    'persons':persons,
    'regions':regions,
    'showdate':showdate,
    'points':points
}

import numpy as np
import pandas as pd
cnbo2021top5=pd.DataFrame(filmdescript,index=films)
cnbo2021top5[['prices','persons']]=cnbo2021top5[['prices','persons']].astype(int)
cnbo2021top5['bos']=cnbo2021top5['bos'].str.replace(',','').astype(int)
cnbo2021top5['showdate']=cnbo2021top5['showdate'].astype('datetime64')
cnbo2021top5['points']=cnbo2021top5['points'].apply(lambda x:float(x) if x!='' else 0)

cnbo2021top5

# 常用調(diào)色盤
r_hex = '#dc2624'     # red,       RGB = 220,38,36	
dt_hex = '#2b4750'    # dark teal, RGB = 43,71,80	
tl_hex = '#45a0a2'    # teal,      RGB = 69,160,162	
r1_hex = '#e87a59'    # red,       RGB = 232,122,89	
tl1_hex = '#7dcaa9'   # teal,      RGB = 125,202,169	
g_hex = '#649E7D'     # green,     RGB = 100,158,125	
o_hex = '#dc8018'     # orange,    RGB = 220,128,24	
tn_hex = '#C89F91'    # tan,       RGB = 200,159,145	
g50_hex = '#6c6d6c'   # grey-50,   RGB = 108,109,108	
bg_hex = '#4f6268'    # blue grey, RGB = 79,98,104	
g25_hex = '#c7cccf'   # grey-25,   RGB = 199,204,207

color=['#dc2624' ,'#2b4750','#45a0a2','#e87a59','#7dcaa9','#649E7D','#dc8018','#C89F91','#6c6d6c','#4f6268','#c7cccf']
sns.set_palette(color)

def sinplot(flip=1):
    x = np.linspace(0, 14, 100)
    for i in range(1, 7):
        plt.plot(x, np.sin(x + i * .5) * (7 - i) * flip)
sinplot()
# 對兩種畫圖進行比較
fig = plt.figure()
sns.set()
sinplot()

plt.rcParams['font.sans-serif']=['SimHei'] # 用來正常顯示中文標簽
plt.rcParams['axes.unicode_minus']=False # 用來正常顯示負號
plt.figure(figsize=(14,8))
plt.title("中國電影票房2021top10")
plt.xlabel("電影名稱")
plt.ylabel("電影票房")
sns.lineplot(data=cnbo2021top5[['bos']])
plt.xticks(rotation=45)

cnbo2021top5ftgb=cnbo2021top5.groupby(['ftypes'])['bos','persons','prices','points'].mean()
cnbo2021top5ftgb=cnbo2021top5ftgb.reset_index().replace()
cnbo2021top5ftgb

### 02 條形圖
plt.figure(figsize=(14,8))
plt.title("中國電影票房2021top10")
sns.barplot(x=cnbo2021top5ftgb['ftypes'],y=cnbo2021top5ftgb['persons'])
plt.xlabel("電影類型")
plt.ylabel("場均人次")
plt.xticks(rotation=45)
plt.show()

### 03 直方圖
plt.figure(figsize=(14,8))
plt.title("中國電影票房2021top10")
sns.histplot(x=cnbo2021top5['bos'],bins=15) # x=cnbo2021top5ftgb['ftypes'],y=cnbo2021top5ftgb['persons']
plt.xlabel("電影類型")
plt.ylabel("場均人次")
plt.xticks(rotation=45)
plt.show()

import pandas as pd 
cnboo=pd.read_excel("cnboNPPD1.xlsx")
cnboo

# 設(shè)定調(diào)色盤
sns.set_palette(color)
sns.palplot(sns.color_palette(color,11)) # 表示11種顏色

sns.set_palette(color)
sns.palplot(sns.color_palette(color,11))
plt.figure(figsize=(25,20))
plt.title('電影票房')
plt.xticks(rotation=45)
sns.barplot(x='TYPE',
            y='PRICE',
            hue='TYPE',
            data=cnboo)

sns.set_palette(color)
sns.palplot(sns.color_palette(color,11))
plt.figure(figsize=(15,10))
plt.title('電影票房')
plt.xticks(rotation=45)
sns.countplot(x='TYPE',data=cnboo)

sns.set_palette(color)
sns.palplot(sns.color_palette(color,11))
plt.figure(figsize=(15,10))
plt.title('電影票房')
plt.xticks(rotation=45)
sns.pointplot(x='TYPE',y='PRICE',data=cnboo)
plt.show()

sns.set_palette(color)
sns.palplot(sns.color_palette(color,11))
plt.figure(figsize=(25,10))
plt.title('電影票房')
plt.xticks(rotation=45)
sns.pointplot(x='TYPE',y='PRICE',hue='REGION',data=cnboo)
plt.show()

### 05 箱型圖
sns.set_palette(color)
sns.palplot(sns.color_palette(color,11))
plt.figure(figsize=(35,10))
plt.title('電影票房')
plt.xticks(rotation=45)
sns.boxplot(x='TYPE',y='PERSONS',hue='REGION',data=cnboo) # ,markers=['^','o'],linestyles=['-','--']
plt.show()
# 圖中的單個點代表在此數(shù)據(jù)當中的異常值

### 06 小提琴圖
sns.set_palette(color)
sns.palplot(sns.color_palette(color,11))
plt.figure(figsize=(35,10))
plt.title('電影票房')
plt.xticks(rotation=45)
sns.violinplot(x='TYPE',y='PRICE',hue='REGION',data=cnboo) # ,markers=['^','o'],linestyles=['-','--']
plt.show()

sns.set_palette(color)
sns.palplot(sns.color_palette(color,11))
plt.figure(figsize=(35,10))
plt.title('電影票房')
plt.xticks(rotation=45)
sns.violinplot(x='PERSONS',y='PRICE',hue='REGION',data=cnboo,orient='h')
plt.show()