吴裕雄 python 数据可视化

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")