#!/usr/bin/python
# -*- coding: <encoding name> -*-
import pymssql # 引入pymssql模块
import pandas as pd
import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
import matplotlib.pyplot as plt
import seaborn as sns # Provides a high level interface for drawing attractive and informative statistical graphics
sns.set()
plt.rcParams['font.sans-serif'] = ['SimHei']
# Matplotlib中设置字体-黑体，解决Matplotlib中文乱码问题
plt.rcParams['axes.unicode_minus'] = False
# 解决Matplotlib坐标轴负号'-'显示为方块的问题
sns.set(font='SimHei')
from subprocess import check_output
import warnings # Ignore warning related to pandas_profiling
warnings.filterwarnings('ignore')
conn = pymssql.connect(host='localhost', user='wonderful', password='wonderful', database='ProcreateV93',charset='GBK')
sql = "select username,o_id,p_id from Oplan"
df0 = pd.read_sql(sql, conn)
df = pd.DataFrame(df0)
des=df.describe()
arr_df = pd.DataFrame(des)
# print(arr_df)
# arr_df.to_csv('F:/工作文档/宋春林/Oplan_describe.csv')
nullsum=pd.isnull(df).sum()
fig = plt.figure()
# 画折线图
ax = fig.add_subplot(111)
ax=df.groupby("username")["o_id"].count().plot(kind="line",title="Matches per season", marker='d',color=['blue'],figsize=(10,3))
plt.ylabel("No. of Matches")
plt.show()
# nullsum.to_csv('F:/工作文档/宋春林/Oplan_nullsum.csv')
# 柱状图
fig = plt.figure()
ax = fig.add_subplot(111)
venue = df.groupby('username')['o_id'].count()
gender_df = df.groupby("username", as_index=True).agg({'o_id':'count'}).rename(columns={'username': 'oid_count'})
print(gender_df.describe())
gender_df.plot.bar(figsize=(10,7))
sns.set(style="darkgrid")
# sns.countplot(x='username',data=gender_df)
print(gender_df)
plt.xlabel('doctor_patientnumber')
plt.title('doctor_patientnumber Distribution')
plt.ylabel('Count')
plt.show()
# ax =gender_df.sort_values(ascending=False).head(10).plot.bar(figsize=(5,3))
conn.close()
