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 pd
import matplotlib as mpl
import 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 pd
import matplotlib as mpl
import 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 pd
import matplotlib as mpl
import 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 json
from 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 json
from 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 json
from 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 json
from 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 json
from 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 json
from 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 json
from 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 json
from 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 json
from 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 json
from 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 json
from 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 json
from 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 json
from 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 json
from pyecharts import Liquid
liquid = Liquid("水球图")
liquid.add("水球",[0.82,0.75])
liquid.render("E:\\liquid.html")
import json
import numpy as np
import 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 json
from 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 json
from 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 json
from 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 json
from 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 json
from 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 json
from 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 json
from 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")
