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# -*- coding: utf-8 -*-
"""
Created on Sat Oct 14 17:03:39 2017
@author: wnma3
"""
import os
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
"""
代码说明：
programmer_1: 制作箱线图
data.boxplot-->数据转为箱线图的字典格式
plt.annotate-->绘图
programmer_2: 计算数据
range-->极差
var-->方差
dis-->四分距
programmer_3: 画出盈利图（比例和数值）
programmer_4: 计算成对相关性
data.corr()-->dataframe中相互之间的相关性
data.corr()[u'百合酱蒸凤爪'] -->dataframe某一项与其他项的相关性
"""
def programmer_1(file_name):
catering_sale = file_name
data = pd.read_excel(catering_sale, index_col=u'日期')
plt.figure()
# 画箱线图
p = data.boxplot(return_type='dict')
x = p['fliers'][0].get_xdata()
y = p['fliers'][0].get_ydata()
y = np.sort(y)
for i in range(len(x)):
# 处理临界情况， i=0时
temp = y[i] - y[i - 1] if i != 0 else -78 / 3
# 添加注释, xy指定标注数据，xytext指定标注的位置（所以需要特殊处理）
plt.annotate(
y[i], xy=(x[i], y[i]), xytext=(x[i] + 0.05 - 0.8 / temp, y[i]))
plt.show()
def programmer_2(file_name):
catering_sale = file_name
data = pd.read_excel(catering_sale, index_col=u'日期')
data = data[(data[u'销量'] > 400) & data[u'销量'] < 5000]
statistics = data.describe()[u'销量']
statistics['range'] = statistics['max'] - statistics['min']
statistics['var'] = statistics['std'] / statistics['mean']
statistics['dis'] = statistics['75%'] - statistics['25%']
print(statistics)
def programmer_3(file_name):
dish_profit = file_name #餐饮菜品盈利数据
data = pd.read_excel(dish_profit, index_col=u'菜品名')
data = data[u'盈利'].copy()
data.sort_values(ascending=False)
plt.figure()
data.plot(kind='bar')
plt.ylabel(u'盈利（元）')
p = 1.0 * data.cumsum() / data.sum()
p.plot(color='r', secondary_y=True, style='-o', linewidth=2)
plt.annotate(
format(p[6], '.4%'),
xy=(6, p[6]),
xytext=(6 * 0.9, p[6] * 0.9),
arrowprops=dict(arrowstyle="->", connectionstyle="arc3,rad=.2"))
plt.ylabel(u'盈利（比例）')
plt.show()
def programmer_4(file_name):
catering_sale = file_name
data = pd.read_excel(catering_sale, index_col=u'日期')
data.corr()
data.corr()[u'百合酱蒸凤爪']
data[u'百合酱蒸凤爪'].corr(data[u'翡翠蒸香茜饺'])
if __name__ == "__main__":
path = os.getcwd()
# programmer_1(path + '/data/catering_sale.xls')
# programmer_2(path + '/data/catering_sale.xls')
# programmer_3(path + '/data/catering_dish_profit.xls')
# programmer_4(path + '/data/catering_sale_all.xls')
pass