import pandas as pd

df = pd.DataFrame( {"林大明":[65,92,78,83,70], "陈聪明":[90,72,76,93,56], "黄美丽":[81,85,91,89,77], "熊小娟":[79,53,47,94,80] } )

print(df)

import pandas as pd

datas = [[65,92,78,83,70], [90,72,76,93,56], [81,85,91,89,77], [79,53,47,94,80]]

indexs = ["林大明", "陈聪明", "黄美丽", "熊小娟"]

columns = ["语文", "数学", "英文", "自然", "社会"]

df = pd.DataFrame(datas, columns=columns, index=indexs)

print(df)

import pandas as pd

datas = [[65,92,78,83,70], [90,72,76,93,56], [81,85,91,89,77], [79,53,47,94,80]]

indexs = ["林大明", "陈聪明", "黄美丽", "熊小娟"]

columns = ["语文", "数学", "英文", "自然", "社会"]

df = pd.DataFrame(datas, columns=columns, index=indexs)

indexs[0] = "林晶辉"

df.index = indexs

columns[3] = "理化"

df.columns = columns

print(df)

import pandas as pd

datas = [[65,92,78,83,70], [90,72,76,93,56], [81,85,91,89,77], [79,53,47,94,80]]

indexs = ["林大明", "陈聪明", "黄美丽", "熊小娟"]

columns = ["语文", "数学", "英文", "自然", "社会"]

df = pd.DataFrame(datas, columns=columns, index=indexs)

print('df["自然"] ->')

print(df["自然"])

print()

print('df[["语文", "数学", "自然"] ->')

print(df[["语文", "数学", "自然"]])

print()

print('df[df.数学>=80] ->')

print(df[df.数学 >= 80])

 

import pandas as pd

datas = [[65,92,78,83,70], [90,72,76,93,56], [81,85,91,89,77], [79,53,47,94,80]]

indexs = ["林大明", "陈聪明", "黄美丽", "熊小娟"]

columns = ["语文", "数学", "英文", "自然", "社会"]

df = pd.DataFrame(datas, columns=columns, index=indexs)

print("df.values：")

print(df.values)

print("陈聪明的成绩(df.values[1])：")

print(df.values[1])

print("陈聪明的英文成绩(df.values[1][2])：")

print(df.values[1][2])

import pandas as pd

datas = [[65,92,78,83,70], [90,72,76,93,56], [81,85,91,89,77], [79,53,47,94,80]]

indexs = ["林大明", "陈聪明", "黄美丽", "熊小娟"]

columns = ["语文", "数学", "英文", "自然", "社会"]

df = pd.DataFrame(datas, columns=columns, index=indexs)

print(df)

print('df.loc["陈聪明", :] ->')

print(df.loc["陈聪明", :])

#print(df.loc["陈聪明"])

print()

print('df.loc["陈聪明"]["数学"] ->')

print(df.loc["陈聪明"]["数学"])

print()

print('df.loc[("陈聪明", "熊小娟") ->')

print(df.loc[("陈聪明", "熊小娟"), :])

print()

print('df.loc[:, "数学"] ->')

print(df.loc[:, "数学"])

print()

print('df.loc[("陈聪明", "熊小娟"), ("数学", "自然")] ->')

print(df.loc[("陈聪明", "熊小娟"), ("数学", "自然")])

print()

print('df.loc["陈聪明":"熊小娟", "数学":"社会"] ->')

print(df.loc["陈聪明":"熊小娟", "数学":"社会"])

print()

print('df.loc[:黄美丽, "数学":"社会"] ->')

print(df.loc[:"黄美丽", "数学":"社会"])

print()

print('df.loc["陈聪明":, "数学":"社会"] ->')

print(df.loc["陈聪明":, "数学":"社会"])

import pandas as pd

datas = [[65,92,78,83,70], [90,72,76,93,56], [81,85,91,89,77], [79,53,47,94,80]]

indexs = ["林大明", "陈聪明", "黄美丽", "熊小娟"]

columns = ["语文", "数学", "英文", "自然", "社会"]

df = pd.DataFrame(datas, columns=columns, index=indexs)

print(df)

print('df.iloc[1, :] ->')

print(df.iloc[1, :])

print()

print('df.iloc[1][1] ->')

print(df.iloc[1][1])

import pandas as pd

datas = [[65,92,78,83,70], [90,72,76,93,56], [81,85,91,89,77], [79,53,47,94,80]]

indexs = ["林大明", "陈聪明", "黄美丽", "熊小娟"]

columns = ["语文", "数学", "英文", "自然", "社会"]

df = pd.DataFrame(datas, columns=columns, index=indexs)

print(df)

print('陈聪明的数学科成绩 ->')

print(df.ix["陈聪明"]["数学"])

print(df.ix["陈聪明"][1])

print(df.ix[1]["数学"])

print(df.ix[1][1])

import pandas as pd

datas = [[65,92,78,83,70], [90,72,76,93,56], [81,85,91,89,77], [79,53,47,94,80]]

indexs = ["林大明", "陈聪明", "黄美丽", "熊小娟"]

columns = ["语文", "数学", "英文", "自然", "社会"]

df = pd.DataFrame(datas, columns=columns, index=indexs)

print(df)

print('最前 2 位学生成绩 ->')

print(df.head(2))

print()

print('最后 2 位学生成绩 ->')

print(df.tail(2))

import pandas as pd

datas = [[65,92,78,83,70], [90,72,76,93,56], [81,85,91,89,77], [79,53,47,94,80]]

indexs = ["林大明", "陈聪明", "黄美丽", "熊小娟"]

columns = ["语文", "数学", "英文", "自然", "社会"]

df = pd.DataFrame(datas, columns=columns, index=indexs)

print(df)

print('df.ix["陈聪明"]["数学"] (原始)：' + str(df.loc["陈聪明"]["数学"]))

df.ix["陈聪明"]["数学"] = 91

print('df.ix["陈聪明"]["数学"] (修改)：' + str(df.loc["陈聪明"]["数学"]))

print()

print('df.ix["陈聪明", :] ->')

df.ix["陈聪明", :] = 80

print(df.ix["陈聪明", :])

import pandas as pd

datas = [[65,92,78,83,70], [90,72,76,93,56], [81,85,91,89,77], [79,53,47,94,80]]

indexs = ["林大明", "陈聪明", "黄美丽", "熊小娟"]

columns = ["语文", "数学", "英文", "自然", "社会"]

df = pd.DataFrame(datas, columns=columns, index=indexs)

print(df)

print('按照数学成绩降序排序 ->')

df1 = df.sort_values(by="数学", ascending=False)

print(df1)

print()

print('按照列标题升序排序 ->')

df2 = df.sort_index(axis=0)

print(df2)

print()

import pandas as pd

datas = [[65,92,78,83,70], [90,72,76,93,56], [81,85,91,89,77], [79,53,47,94,80]]

indexs = ["林大明", "陈聪明", "黄美丽", "熊小娟"]

columns = ["语文", "数学", "英文", "自然", "社会"]

df = pd.DataFrame(datas, columns=columns, index=indexs)

print(df)

print('删除陈聪明成绩 ->')

df1 = df.drop("陈聪明")

print(df1)

print()

print('删除数学成绩 ->')

df2 = df.drop("数学", axis=1)

print(df2)

print()

print('删除数学及自然成绩 ->')

df3 = df.drop(["数学", "自然"], axis=1)

print(df3)

print()

print('删除从陈聪明到熊小娟成绩 ->')

df4 = df.drop(df.index[1:4])

print(df4)

print()

print('删除从数学到自然的成绩 ->')

df5 = df.drop(df.columns[1:4], axis=1)

print(df5)

print()

import pandas as pd

dt = pd.read_html("http://www.86pm25.com/city/beijing.html")

data=dt[0]

print(data)

import pandas as pd

tables = pd.read_html("http://value500.com/M2GDP.html")

n = 1

for table in tables:

print("第 " + str(n) + " 个表格：")

print(table.head())

print()

n += 1

 

import pandas as pd

tables = pd.read_html("http://value500.com/M2GDP.html")

table = tables[18]

table = table.drop(table.index[0:1])

table.columns = ["年份", "M2指标", "GDP绝对额", "M2/GDP"]

table.index = range(len(table.index))

print(table)

import pandas as pd

from pylab import *

rcParams['font.sans-serif'] = ['SimHei'] #设置中文显示

datas = [[65,92,78,83,70], [90,72,76,93,56], [81,85,91,89,77], [79,53,47,94,80]]

indexs = ["林大明", "陈聪明", "黄美丽", "熊小娟"]

columns = ["语文", "数学", "英文", "自然", "社会"]

df = pd.DataFrame(datas, columns=columns, index=indexs)

df.plot()

def rbCity(): #单击区县按钮的处理函数

global sitelist, listradio

sitelist.clear() #清除原有监测站点列表

for r in listradio: #删除原有监测站点按钮

r.destroy()

n=0

for c1 in data["监测站点"]: #逐一取出所选区县市的监测站点

if(c1 == city.get()):

sitelist.append(data.ix[n, 1])

n += 1

sitemake() #生成测站点按钮

rbSite() #显示PM2.5数值

def rbSite(): #单击监测站按钮后的处理函数

n = 0

for s in data.ix[:,1]: #逐一取得监测站点

if(s == site.get()): #如果某监测站点名称与选中的监测站点相同，则

pm = data.ix[n][ "PM2.5浓度"] #取得该站点的PM2.5数值

print(pm)

pm=pm[:-5] #去除数据后面的5位单位字符

pm=int(pm) #把PM2.5的字符型数据转为整型

if(pd.isnull(pm)): #如果没有数据，则

result1.set(s + "站的 PM2.5 值当前无数据！") #显示无数据

else: #如果有数据，则

if(pm <= 35): #转换为空气质量等级

grade1 = "优秀"

elif(pm <= 53):

grade1 = "良好"

elif(pm <= 70):

grade1 = "中等"

else:

grade1 = "差"

result1.set(s + "站的 PM2.5 值为" + str(pm) + ";" + grade1 )

break #找到选中的监测站点的数据后就跳出循环

n += 1

def clickRefresh(): #重新读取数据

global data

df = pd.read_html("http://www.86pm25.com/city/beijing.html")

data=df[0]

rbSite() #更新监测站点的数据

def sitemake(): #建立监测站点按钮

global sitelist, listradio

for c1 in sitelist: #逐一建立按钮

rbtem = tk.Radiobutton(frame2, text=c1, variable=site, value=c1, command=rbSite) #建立单选按钮

listradio.append(rbtem) #插入至按钮列表

if(c1==sitelist[0]): #默认选取第1个按钮

rbtem.select()

rbtem.pack(side="left") #靠左对齐

import tkinter as tk

import pandas as pd

df = pd.read_html("http://www.86pm25.com/city/beijing.html")

data=df[0]

win=tk.Tk()

win.geometry("640x270")

win.title("PM2.5 实时监测")

city = tk.StringVar() #区县名称变量

site = tk.StringVar() #监测站点名称变量

result1 = tk.StringVar() #显示信息变量

citylist = [] #区县列表

sitelist = [] #监测站点列表

listradio = [] #区县按钮列表

#建立区县列表

for c1 in data["监测站点"]:

if(c1 not in citylist): #如果列表中不存在该县区就将该县区名称插入列表

citylist.append(c1)

#建立第1个区县的监测站点列表

count = 0

for c1 in data["监测站点"]:

if(c1 == citylist[0]): #如果是第1个区县，则

sitelist.append(data.ix[count, 1]) #把该区县的所有监测站点插入到监测站点列表

count += 1

label1 = tk.Label(win, text="区县：", pady=6, fg="blue", font=("新细明体", 12))

label1.pack()

frame1 = tk.Frame(win) #区县容器

frame1.pack()

for i in range(0,2): #按钮分2行

for j in range(0,8): #每行8个

n = i * 8 + j #第n个按钮

if(n < len(citylist)):

city1 = citylist[n] #取得区县名称

rbtem = tk.Radiobutton(frame1, text=city1, variable=city, value=city1, command=rbCity) #建立单选按钮

rbtem.grid(row=i, column=j) #设置按钮的位置

if(n==0): #选取第1个区县

rbtem.select()

label2 = tk.Label(win, text="监测站点：", pady=6, fg="blue", font=("新细明体", 12))

label2.pack()

frame2 = tk.Frame(win) #监测站点容器

frame2.pack()

sitemake()

btnDown = tk.Button(win, text="更新数据", font=("新细明体", 12), command=clickRefresh)

btnDown.pack(pady=6)

lblResult1 = tk.Label(win, textvariable=result1, fg="red", font=("新细明体", 16))

lblResult1.pack(pady=6)

rbSite() #显示测站讯息

win.mainloop()

def rbCity(): #點選縣市選項按鈕後處理函式

global sitelist, listradio

sitelist.clear() #清除原有測站串列

for r in listradio: #移除原有測站選項按鈕

r.destroy()

n=0

for c1 in data["County"] == city.get(): #逐一取出選取縣市的測站

if(c1 == True):

sitelist.append(data.ix[n, 0])

n += 1

sitemake() #建立測站選項按鈕

rbSite() #顯示PM2.5訊息

def rbSite(): #點選測站選項按鈕後處理函式

n = 0

for s in data.ix[:, 0]: #逐一取得測站

if(s == site.get()): #取得點選的測站

pm = data.ix[n, "PM2.5"] #取得PM2.5的值

if(pd.isnull(pm)): #如果沒有資料

result1.set(s + "站的 PM2.5 值目前無資料！")

else: #如果有資料

if(pm <= 35): #轉換為等級

grade1 = "低"

elif(pm <= 53):

grade1 = "中"

elif(pm <= 70):

grade1 = "高"

else:

grade1 = "非常高"

result1.set(s + "站的 PM2.5 值為「" + str(pm) + "」：「" + grade1 + "」等級")

break #找到點選測站就離開迴圈

n += 1

def clickRefresh(): #重新讀取資料

global data

# data = pd.read_csv("http://opendata.epa.gov.tw/ws/Data/REWXQA/?$orderby=SiteName&$skip=0&$top=1000&format=csv")

data = pd.read_csv("F:\\pythonBase\\pythonex\\ch09\\AQX_20160927145712.csv")

rbSite() #更新測站資料

def sitemake(): #建立測站選項按鈕

global sitelist, listradio

for c1 in sitelist: #逐一建立選項按鈕

rbtem = tk.Radiobutton(frame2, text=c1, variable=site, value=c1, command=rbSite) #建立選項按鈕

listradio.append(rbtem) #加入選項按鈕串列

if(c1==sitelist[0]): #預設選取第1個項目

rbtem.select()

rbtem.pack(side="left") #靠左排列

import tkinter as tk

import pandas as pd

# data = pd.read_csv("http://opendata.epa.gov.tw/ws/Data/REWXQA/?$orderby=SiteName&$skip=0&$top=1000&format=csv")

data = pd.read_csv("F:\\pythonBase\\pythonex\\ch09\\AQX_20160927145712.csv")

win=tk.Tk()

win.geometry("640x270")

win.title("PM2.5 實時監測")

city = tk.StringVar() #縣市文字變數

site = tk.StringVar() #測站文字變數

result1 = tk.StringVar() #訊息文字變數

citylist = [] #縣市串列

sitelist = [] #鄉鎮串列

listradio = [] #鄉鎮選項按鈕串列

#建立縣市串列

for c1 in data["County"]:

if(c1 not in citylist): #如果串列中無該縣市就將其加入

citylist.append(c1)

#建立第1個縣市的測站串列

count = 0

for c1 in data["County"]:

if(c1 == citylist[0]): #是第1個縣市的測站

sitelist.append(data.ix[count, 0])

count += 1

label1 = tk.Label(win, text="縣市：", pady=6, fg="blue", font=("新細明體", 12))

label1.pack()

frame1 = tk.Frame(win) #縣市容器

frame1.pack()

for i in range(0,3): #3列選項按鈕

for j in range(0,8): #每列8個選項按鈕

n = i * 8 + j #第n個選項按鈕

if(n < len(citylist)):

city1 = citylist[n] #取得縣市名稱

rbtem = tk.Radiobutton(frame1, text=city1, variable=city, value=city1, command=rbCity) #建立選項按鈕

rbtem.grid(row=i, column=j) #設定選項按鈕位置

if(n==0): #選取第1個縣市

rbtem.select()

label2 = tk.Label(win, text="測站：", pady=6, fg="blue", font=("新細明體", 12))

label2.pack()

frame2 = tk.Frame(win) #測站容器

frame2.pack()

sitemake()

btnDown = tk.Button(win, text="更新資料", font=("新細明體", 12), command=clickRefresh)

btnDown.pack(pady=6)

lblResult1 = tk.Label(win, textvariable=result1, fg="red", font=("新細明體", 16))

lblResult1.pack(pady=6)

rbSite() #顯示測站訊息

win.mainloop()