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holoviews是一个超级简洁的python可视化工具，后端为bokeh、matplotlib、datashader库，最擅长干的是一行代码搞定一张图(类似seaborn)，如下文的河流图(Sankey)；
HoloViews helps you understand your data better, by letting you work seamlessly with both the data and its graphical representation.
目录
01 - 精彩demo
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import pandas
as pd
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import holoviews
as hv
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hv.extension(
'matplotlib')
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edges_df = pd.read_csv(
'fb_edges.csv')
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nodes_df = pd.read_csv(
'fb_nodes.csv')
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fb_nodes = hv.Nodes(nodes_df).sort()
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fb_graph = hv.Graph((edges_df, fb_nodes), label=
'Facebook Circles')
#绘图
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fb_graph.opts(cmap=
'Set1',
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node_color=
'circle',
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fig_size=
350,
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show_frame=
False,
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xaxis=
None,
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yaxis=
None,
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node_size=
10)
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edges = pd.read_csv(
'energy.csv')
#导入数据
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sankey = hv.Sankey(edges, label=
'Energy Diagram')
#绘图
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sankey.opts(label_position=
'left',
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edge_color=
'target',
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node_color=
'index',
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cmap=
'set1')
#图形属性设置
hv.Sankey(edges, label='Energy Diagram') 一行代码搞定小面的河流图～～
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# 矩阵图
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import holoviews
as hv
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from holoviews
import opts
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hv.extension(
'bokeh')
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from bokeh.sampledata.iris
import flowers
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from holoviews.operation
import gridmatrix
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ds = hv.Dataset(flowers)
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grouped_by_species = ds.groupby(
'species', container_type=hv.NdOverlay)
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grid = gridmatrix(grouped_by_species, diagonal_type=hv.Scatter)
#绘图
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grid.opts(opts.Scatter(tools=[
'hover',
'box_select'], bgcolor=
'#efe8e2', fill_alpha=
0.2, size=
4))
02 - 快速上手holoviews
holoviews安装
pip install holoviews -i https://pypi.tuna.tsinghua.edu.cn/simple从scatter开始
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import pandas
as pd
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import numpy
as np
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import holoviews
as hv
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from holoviews
import opts
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hv.extension(
'bokeh',
'matplotlib')
#导入扩展'bokeh','matplotlib'
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station_info = pd.read_csv(
'station_info.csv')
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hv.Scatter(station_info,
'services',
'ridership')
#轻松绘制散点图
使用“+”添加Layout
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# 使用“+”添加Layout
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hv.Scatter(station_info,
'services',
'ridership') + \
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hv.Histogram(
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np.histogram(station_info[
'opened'], bins=
24), kdims=[
'opened'])+\
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hv.Scatter(station_info,
'services',
'ridership')
使用“*”添加Overlay
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# 使用“*”添加Overlay
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taxi_dropoffs = {
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hour: arr
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for hour, arr
in np.load(
'hourly_taxi_data.npz').items()
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}
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bounds = (
-74.05,
40.70,
-73.90,
40.80)
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image = hv.Image(taxi_dropoffs[
'0'], [
'lon',
'lat'], bounds=bounds)
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points = hv.Points(station_info, [
'lon',
'lat'])
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image + image * points
添加交互小部件
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# 添加交互小部件
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dictionary = {
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int(hour): hv.Image(arr, [
'lon',
'lat'], bounds=bounds)
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for hour, arr
in taxi_dropoffs.items()
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}
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hv.HoloMap(dictionary, kdims=
'Hour')
使用opts个性化图形设置
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# 默认bokeh后端
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spike_train = pd.read_csv(
'spike_train.csv.gz')
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curve = hv.Curve(spike_train,
'milliseconds',
'Hertz')
# 折线图
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spikes = hv.Spikes(spike_train,
'milliseconds', [])
# 条形码
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layout = curve + spikes
#
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layout
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#opts个性化图形属性设置
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layout.opts(
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#Options
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opts.Curve(height=
200,
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width=
900,
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xaxis=
None,
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line_width=
1.50,
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color=
'red',
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tools=[
'hover']),
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opts.Spikes(height=
150,
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width=
900,
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yaxis=
None,
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line_width=
0.25,
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color=
'grey')).cols(
1)
更多精彩
https://github.com/holoviz/holoviews
转载：https://blog.csdn.net/qq_21478261/article/details/115425925
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