import pandas as pd

df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv")print(df.head())data = df.drop(["宝贝","卖家"],axis=1).groupby(["位置"]).mean().sort_values(["成交量"],ascending=False)print(data.head())

import pandas as pdimport matplotlib as mplimport matplotlib.pyplot as plt

df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv")data_mean = df.drop(["宝贝","卖家"],axis=1).groupby(["位置"]).mean().sort_values(["成交量"],ascending=False)print(data_mean.head())

mpl.style.use("ggplot")fig,(ax1,ax2) = plt.subplots(1,2,figsize=(12,4))data_mean.价格.plot(kind="barh",ax=ax1)ax1.set_xlabel("各省份平均价格")data_mean.成交量.plot(kind="barh",ax=ax2)ax2.set_xlabel("各省份平均成交量")fig.tight_layout()plt.show()

import pandas as pdimport matplotlib as mplimport matplotlib.pyplot as plt

df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv")data_mean = df.drop(["宝贝","卖家"],axis=1).groupby(["位置"]).mean().sort_values(["成交量"],ascending=False)print(data_mean.head())s = data_mean.成交量mpl.style.use("ggplot")fig,axes = plt.subplots(2,2,figsize=(10,10))s.plot(ax=axes[0][0],kind="line",title="line")s.plot(ax=axes[0][1],kind="bar",title="bar")s.plot(ax=axes[1][0],kind="box",title="box")s.plot(ax=axes[1][1],kind="pie",title="pie")fig.tight_layout()plt.show()

import pandas as pdimport matplotlib as mplimport matplotlib.pyplot as plt

df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv")a = df.价格b = df.成交量mpl.style.use("ggplot")fig,axes = plt.subplots(1,1,figsize=(12,4))axes.scatter(a,b)axes.set_xlabel("价格")axes.set_ylabel("成交量")fig.tight_layout()plt.show()

import jsonfrom pyecharts import Pie

f = open("F:\\python3_pachongAndDatareduce\\data\\pyecharts JSONData\\datas\\pies.json")data = json.load(f)print(data)name = data["name"]print(name)sales = data["sales"]print(sales)sales_volume = data["sales_volume"]print(sales_volume)

import jsonfrom pyecharts import Pie

f = open("F:\\python3_pachongAndDatareduce\\data\\pyecharts JSONData\\datas\\pies.json")data = json.load(f)name = data["name"]sales = data["sales"]sales_volume = data["sales_volume"]pie = Pie("衣服清洗剂市场占比",title_pos="left",width=800)pie.add("成交量",name,sales_volume,center=[25,50],is_random=True,radius=[30,75],rosetype="radius")pie.add("销售额",name,sales,center=[75,50],is_random=True,radius=[30,75],rosetype="area",is_legend_show=True,is_label_show=True)pie.show_config()pie.render("E:\\rose.html")

import jsonfrom pyecharts import Pie

f = open("F:\\python3_pachongAndDatareduce\\data\\pyecharts JSONData\\datas\\pies.json")data = json.load(f)name = data["name"]sales = data["sales"]sales_volume = data["sales_volume"]pie = Pie("",width=800)pie.add("",name,sales,is_label_show=True)pie.render("E:\\pie.html")

import jsonfrom pyecharts import Funnel

f = open("F:\\python3_pachongAndDatareduce\\data\\pyecharts JSONData\\datas\\pies.json")data = json.load(f)name = data["name"]sales = data["sales"]sales_volume = data["sales_volume"]funnle = Funnel("",width=800)funnle.add("成交量",name,sales_volume,is_label_show=True,label_pos="inside",label_text_color="#fff")funnle.render("E:\\funnle.html")

import jsonfrom pyecharts import Bar

f = open("F:\\python3_pachongAndDatareduce\\data\\pyecharts JSONData\\datas\\pies.json")data = json.load(f)name = data["name"]sales = data["sales"]sales_volume = data["sales_volume"]bar = Bar("衣服清洗剂市场占比柱形图",width=800)bar.add("成交量",name,sales_volume,center=[25,50],mark_point=["average"])bar.add("销售额",name,sales,center=[25,50],mark_point=["max","min"])bar.render("E:\\bar.html")

import jsonfrom pyecharts import Bar

f = open("F:\\python3_pachongAndDatareduce\\data\\pyecharts JSONData\\datas\\pies.json")data = json.load(f)name = data["name"]sales = data["sales"]sales_volume = data["sales_volume"]bar = Bar("衣服清洗剂市场占比柱形图",width=800)bar.add("成交量",name,sales_volume,center=[25,50],mark_point=["average"],is_stack=True)bar.add("销售额",name,sales,center=[25,50],mark_point=["max","min"],is_stack=True)bar.render("E:\\bar01.html")

import jsonfrom pyecharts import Bar

f = open("F:\\python3_pachongAndDatareduce\\data\\pyecharts JSONData\\datas\\pies.json")data = json.load(f)name = data["name"]sales = data["sales"]sales_volume = data["sales_volume"]bar = Bar("衣服清洗剂市场占比柱形图",width=800)bar.add("成交量",name,sales_volume,center=[25,50],mark_point=["average"],is_stack=True,is_convert=True)bar.add("销售额",name,sales,center=[25,50],mark_point=["max","min"],is_stack=True,is_convert=True)bar.render("E:\\bar_convert.html")

import jsonfrom pyecharts import Bar

f = open("F:\\python3_pachongAndDatareduce\\data\\pyecharts JSONData\\datas\\lines.json")data = json.load(f)print(data)date = data["date"]print(date)sales1 = data["sales1"]print(sales1)sales2 = data["sales2"]print(sales2)

import jsonfrom pyecharts import Line

f = open("F:\\python3_pachongAndDatareduce\\data\\pyecharts JSONData\\datas\\lines.json")data = json.load(f)date = data["date"]sales1 = data["sales1"]sales2 = data["sales2"]line = Line("洗衣液月销售情况")line.add("成交量",date,sales1,mark_point=["average","max","min"],mark_point_symbol="diamond",mark_point_textcolor="#40ff27")line.add("销售额",date,sales2,mark_point=["max"],is_smooth=True,mark_line=["max","average"],mark_point_symbol="arrow",mark_point_symbolsize=40)line.render("E:\\line.html")

import jsonfrom pyecharts import Line

f = open("F:\\python3_pachongAndDatareduce\\data\\pyecharts JSONData\\datas\\lines.json")data = json.load(f)date = data["date"]sales1 = data["sales1"]sales2 = data["sales2"]line = Line("洗衣液月销售情况")line.add("成交量",date,sales1,mark_point=["average","max","min"],mark_point_symbol="diamond",is_label_show=True)line.add("销售额",date,sales2,mark_point=["max"],is_stack=True,mark_line=["max","average"],is_label_show=True)line.render("E:\\linestate.html")

import jsonfrom pyecharts import Line

f = open("F:\\python3_pachongAndDatareduce\\data\\pyecharts JSONData\\datas\\lines.json")data = json.load(f)date = data["date"]sales1 = data["sales1"]sales2 = data["sales2"]line = Line("洗衣液月销售情况")line.add("成交量",date,sales1,is_step=True,is_label_show=True)line.add("销售额",date,sales2,is_step=True,is_label_show=True)line.render("E:\\linestep.html")

import jsonfrom pyecharts import Line

f = open("F:\\python3_pachongAndDatareduce\\data\\pyecharts JSONData\\datas\\lines.json")data = json.load(f)date = data["date"]sales1 = data["sales1"]sales2 = data["sales2"]line = Line("洗衣液月销售情况")line.add("成交量",date,sales1,is_fill=True,area_opacity=0.4)line.add("销售额",date,sales2,is_fill=True,area_opacity=0.2,area_color="#000")line.render("E:\\linefill.html")

import jsonfrom pyecharts import Gauge

gauge = Gauge("目标完成率")gauge.add("任务指标","完成率",80.2)gauge.render("E:\\gauge.html")

import jsonfrom pyecharts import Liquid

liquid = Liquid("水球图")liquid.add("水球",[0.82,0.75])liquid.render("E:\\liquid.html")

import jsonimport numpy as npimport pandas as pd

from pyecharts import WordCloud

wd = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\cp.csv",header=0)print(np.shape(wd))print(wd.head())catename = [i[0] for i in wd[["关键词"]].values]value = [int(i[0]) for i in wd[["词频"]].values]wordcloud = WordCloud(width=1200,height=600)wordcloud.add("",catename,value,word_size_range=[10,120],shape="star")wordcloud.render("E:\\wordcloud.html")

import jsonfrom pyecharts import Line

f = open("F:\\python3_pachongAndDatareduce\\data\\pyecharts JSONData\\datas\\scatters.json")data = json.load(f)print(data)xs = data["xs"]print(xs)gb = data["gb"]print(gb)

import jsonfrom pyecharts import Scatter

f = open("F:\\python3_pachongAndDatareduce\\data\\pyecharts JSONData\\datas\\scatters.json")data = json.load(f)xs = data["xs"]gb = data["gb"]scatter = Scatter("销售额与高质量宝贝数")scatter.add("关系",xs,gb)scatter.render("E:\\scatter.html")

from pyecharts import Boxplot

x_axis = ["销售额"]y_axis = [[169,126,248,263,265,273,248,241,326,334,479,347]]

boxplot = Boxplot("箱形图")_yaxis = boxplot.prepare_data(y_axis)boxplot.add("boxplot",x_axis,_yaxis)boxplot.render("E:\\boxplot.html")

import jsonfrom pyecharts import Bar,Line,Overlap

f = open("F:\\python3_pachongAndDatareduce\\data\\pyecharts JSONData\\datas\\overlaps.json")data = json.load(f)print(data)date = data["date"]print(date)sales1 = data["sales1"]print(sales1)sales2 = data["sales2"]print(sales2)

import jsonfrom pyecharts import Bar,Line,Overlap

f = open("F:\\python3_pachongAndDatareduce\\data\\pyecharts JSONData\\datas\\overlaps.json")data = json.load(f)date = data["date"]sales1 = data["sales1"]sales2 = data["sales2"]

bar = Bar("Line-Bar")bar.add("Bar",date,sales1)line = Line()line.add("Line",date,sales2)

overlap = Overlap()overlap.add(bar)overlap.add(line)overlap.render("E:\\linebar.html")

import jsonfrom pyecharts import Bar3D

f = open("F:\\python3_pachongAndDatareduce\\data\\pyecharts JSONData\\datas\\bar3ds.json")datas = json.load(f)x_axis = datas["x_axis"]y_axis = datas["y_axis"]data = datas["data"]range_color = datas["range_color"]

bar3d = Bar3D("3D柱状图",width=1200,height=600)bar3d.add("",x_axis,y_axis,[[d[1],d[0],d[2]] for d in data],is_visualmap=True,visual_range=[0,20],visual_range_color=range_color)bar3d.render("E:\\3dbar.html")

import jsonfrom pyecharts import Bar3D

f = open("F:\\python3_pachongAndDatareduce\\data\\pyecharts JSONData\\datas\\bar3ds.json")datas = json.load(f)x_axis = datas["x_axis"]y_axis = datas["y_axis"]data = datas["data"]range_color = datas["range_color"]

bar3d = Bar3D("3D柱状图",width=1200,height=600)bar3d.add("",x_axis,y_axis,[[d[1],d[0],d[2]] for d in data],is_visualmap=True,visual_range=[0,20], visual_range_color=range_color,grid3d_width=200,grid3d_depth=80,is_grid3d_roate=True)bar3d.render("E:\\3dbar01.html")

import jsonfrom pyecharts import Bar3D

f = open("F:\\python3_pachongAndDatareduce\\data\\pyecharts JSONData\\datas\\bar3ds.json")datas = json.load(f)x_axis = datas["x_axis"]y_axis = datas["y_axis"]data = datas["data"]range_color = datas["range_color"]

bar3d = Bar3D("3D柱状图",width=1200,height=600)bar3d.add("",x_axis,y_axis,[[d[1],d[0],d[2]] for d in data],is_visualmap=True,visual_range=[0,20], visual_range_color=range_color,grid3d_width=200,grid3d_depth=80,is_grid3d_speed=180)bar3d.render("E:\\3dbar02.html")