问题描述
我用pyecharts进行了绘制,但最终修改了直接生成的html文件,因此在此问题中添加了两个标签
问题:我正在尝试绘制带有pyecharts的折线图,其数据如下所示:
x_data = [1596704736000,1596705336000,1596705937000,1596706538000,...]
y_data = [12,4,5,...]
其中x_data是时间戳。我用pyecharts进行了绘制,并且dataZoom选项是:
datazoom_opts=[opts.DataZoomOpts(start_value=s_tamp - 60*60*1000,end_value=e_tamp + 60*60*1000,range_start=0,range_end=100),],
这是图片:
如图所示,dataZoom从1970开始,实际数据从1596704736000(即2020/8/6)开始。
我的努力:
结果:只有dataZoom滚动条变短了,范围仍然从1970开始。
- 我将xAxis数据类型从“时间”更改为“类别”,“值”
结果:
- 我将时间戳输入更改为datetime
结果:dataZoom仍然从1970开始
- 我在dataZoom中添加了
rangeMode: value
结果:缩放栏的末端变得很小,并以我的数据范围显示了该图,但是该栏的范围仍然以1970开始
HTML代码太长,我将发布这两个的xaxis选项和datazoom选项以及pyecharts选项
...
"xAxis": [
{
"type": "time","show": true,"scale": false,"nameLocation": "end","nameGap": 15,"interval": 21600000.0,"gridindex": 0,"inverse": false,"offset": 0,"splitNumber": 5,"min": 1596700714000,"max": 1597139914000,"minInterval": 0,"splitLine": {
"show": false,"linestyle": {
"show": true,"width": 1,"opacity": 1,"curveness": 0,"type": "solid"
}
},...
"dataZoom": [
{
"show": true,"type": "slider","realtime": true,"startValue": 1596703383000,"endValue": 159714258300,"start": 0,"end": 100,"orient": "horizontal","zoomlock": false,"filterMode": "filter"
}
]
,这是xaxis的pyecharts设置。之前提到了dataZoom pyecharts设置。
xaxis_opts=opts.AxisOpts(
type_ = 'time',min_ = s_tamp - 60*60*1000,# the start time timestampe - 1 hour
max_ = e_tamp + 60*60*1000,# the end time timestampe + 1 hour
interval = 5*24*60*60*1000/(5*4) # 5 days interval
)
有人对此有任何线索吗?如果信息不足以解决问题,请先发表评论告知我。
解决方法
我遇到了类似的问题,在xAxis选项中添加is_scale=True
对我来说很有效。
xaxis_opts = opts.AxisOpts(
type_='time',is_scale=True,)
完整示例:
from pyecharts.charts import Line
from pyecharts import options as opts
line = Line()
xaxis_opts = opts.AxisOpts(
type_='time',)
yaxis_opts = opts.AxisOpts(
type_='value'
)
datazoom_opts = opts.DataZoomOpts(
type_='slider',start_value=1596705336000,end_value=1596706538000,)
line.add_xaxis(
[1596704736000,1596705336000,1596705937000,1596706538000,1596707538000])
line.add_yaxis('values',[0,1,2,3,4])
line.set_global_opts(
xaxis_opts=xaxis_opts,yaxis_opts=yaxis_opts,datazoom_opts=datazoom_opts
)
print(line.dump_options())
line.render()
结果: