//導(dǎo)入柱狀圖-Bar
from pyecharts import Bar
//設(shè)置行名
columns = ["Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"]
//設(shè)置數(shù)據(jù)
data1 = [2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3]
data2 = [2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3]
//設(shè)置柱狀圖的主標(biāo)題與副標(biāo)題
bar = Bar("柱狀圖", "一年的降水量與蒸發(fā)量")
//添加柱狀圖的數(shù)據(jù)及配置項(xiàng)
bar.add("降水量", columns, data1, mark_line=["average"], mark_point=["max", "min"])
bar.add("蒸發(fā)量", columns, data2, mark_line=["average"], mark_point=["max", "min"])
//生成本地文件（默認(rèn)為.html文件）
bar.render()

//導(dǎo)入餅圖Pie
from pyecharts import Pie
//設(shè)置主標(biāo)題與副標(biāo)題，標(biāo)題設(shè)置居中，設(shè)置寬度為900
pie = Pie("餅狀圖", "一年的降水量與蒸發(fā)量",title_pos='center',width=900)
//加入數(shù)據(jù)，設(shè)置坐標(biāo)位置為【25，50】，上方的colums選項(xiàng)取消顯示
pie.add("降水量", columns, data1 ,center=[25,50],is_legend_show=False)
//加入數(shù)據(jù)，設(shè)置坐標(biāo)位置為【75，50】，上方的colums選項(xiàng)取消顯示，顯示label標(biāo)簽
pie.add("蒸發(fā)量", columns, data2 ,center=[75,50],is_legend_show=False,is_label_show=True)
//保存圖表
pie.render()

//導(dǎo)入箱型圖Boxplot
from pyecharts import Boxplot 
boxplot = Boxplot("箱形圖", "一年的降水量與蒸發(fā)量")
x_axis = ['降水量','蒸發(fā)量']
y_axis = [data1,data2]
//prepare_data方法可以將數(shù)據(jù)轉(zhuǎn)為嵌套的 [min, Q1, median (or Q2), Q3, max]
yaxis = boxplot.prepare_data(y_axis) 
boxplot.add("天氣統(tǒng)計(jì)", x_axis, _yaxis)
boxplot.render()

from pyecharts import Line
line = Line("折線圖","一年的降水量與蒸發(fā)量")
//is_label_show是設(shè)置上方數(shù)據(jù)是否顯示
line.add("降水量", columns, data1, is_label_show=True)
line.add("蒸發(fā)量", columns, data2, is_label_show=True)
line.render()

from pyecharts import Radar
radar = Radar("雷達(dá)圖", "一年的降水量與蒸發(fā)量")
//由于雷達(dá)圖傳入的數(shù)據(jù)得為多維數(shù)據(jù)，所以這里需要做一下處理
radar_data1 = [[2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3]]
radar_data2 = [[2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3]]
//設(shè)置column的最大值，為了雷達(dá)圖更為直觀，這里的月份最大值設(shè)置有所不同
schema = [
("Jan", 5), ("Feb",10), ("Mar", 10),
("Apr", 50), ("May", 50), ("Jun", 200),
("Jul", 200), ("Aug", 200), ("Sep", 50),
("Oct", 50), ("Nov", 10), ("Dec", 5)
]
//傳入坐標(biāo)
radar.config(schema)
radar.add("降水量",radar_data1)
//一般默認(rèn)為同一種顏色，這里為了便于區(qū)分，需要設(shè)置item的顏色
radar.add("蒸發(fā)量",radar_data2,item_color="#1C86EE")
radar.render()

from pyecharts import Scatter
scatter = Scatter("散點(diǎn)圖", "一年的降水量與蒸發(fā)量")
//xais_name是設(shè)置橫坐標(biāo)名稱，這里由于顯示問題，還需要將y軸名稱與y軸的距離進(jìn)行設(shè)置
scatter.add("降水量與蒸發(fā)量的散點(diǎn)分布", data1,data2,xaxis_name="降水量",yaxis_name="蒸發(fā)量",
 yaxis_name_gap=40)
scatter.render()

from pyecharts import Grid
//設(shè)置折線圖標(biāo)題位置
line = Line("折線圖","一年的降水量與蒸發(fā)量",title_top="45%")
line.add("降水量", columns, data1, is_label_show=True)
line.add("蒸發(fā)量", columns, data2, is_label_show=True)
grid = Grid()
//設(shè)置兩個圖表的相對位置
grid.add(bar, grid_bottom="60%")
grid.add(line, grid_top="60%")
grid.render()

from pyecharts import Overlap
overlap = Overlap()
bar = Bar("柱狀圖-折線圖合并", "一年的降水量與蒸發(fā)量")
bar.add("降水量", columns, data1, mark_point=["max", "min"])
bar.add("蒸發(fā)量", columns, data2, mark_point=["max", "min"])
overlap.add(bar)
overlap.add(line)
overlap.render()