hvplot

问题 I try to create a grouped bar plot but can't figure out how to influence the order of the barplot. Given these example data: import pandas as pd import hvplot.pandas df = pd.DataFrame({ "lu": [200, 100, 10], "le": [220, 80, 130], "la": [60, 20, 15], "group": [1, 2, 2], }) df = df.groupby("group").sum() I'd like to create a horizontal grouped bar plot showing the two groups 1 and 2 with all three columns. The columns should appear in the order of "le", "la" and "lu". Naturally I'd try this

问题 When I use pandas df.plot() it has matplotlib as a default plotting backend. But this creates static plots. I would like interactive plots, so I have to change the pandas plotting background. How do I do change the plotting backend of pandas to have a different library creating my plots when i use .plot()? 回答1: You need pandas >= 0.25 to change the plotting backend of pandas. The available plotting backends are: matplotlib hvplot >= 0.5.1 holoviews pandas_bokeh plotly >= 4.8 altair So, the

问题 Using the hvplot tutorial we are trying to generate a bar plot with values as labels on the bars itself. The bar plot is generated using the following code import dask.dataframe as dd import hvplot.pandas df = dd.read_parquet('data/earthquakes.parq').persist() df.magType.value_counts().compute().to_frame().hvplot.bar() How can we add the value of the bars on the bar itself? 回答1: Use holoviews hv.Labels() to add value labels to your data. You create the labels separately and use the * symbol

问题 The libraries of the Holoviz ecosystem are continuously updated. Using pip, how do I install the latest git versions of: Holoviews Hvplot Panel Datashader Param 回答1: The latest github versions of the holoviz libraries can be installed as follows. Holoviews: pip install git+https://github.com/holoviz/holoviews.git Hvplot: pip install git+https://github.com/holoviz/hvplot.git Panel: pip install git+https://github.com/holoviz/panel.git Datashader: pip install git+https://github.com/holoviz

问题 I want a scatter plot of different types of "asset", each asset should have the same color and labeled in the legend. I can do this using an NdOverlay of Scatter. Then I want to overlay two such plots, eg one coming from a model and another from experiment, so that the first and second only change in marker but keeps the same color for each asset. I would expect this to work df1 = pd.DataFrame({"asset": ["A", "B", "B"], "x": [1,2,3], "y": [1,2,3]}) df2 = pd.DataFrame({"asset": ["A", "B", "B"]

问题 I have been lately working with bokeh for plotting. I just found out about holoviews and wanted to plot a basic box plot. In my box plot I am trying to color per one of the categories I am grouping the data in. Here is the code I am using: hv.extension('bokeh') %opts BoxWhisker (box_color='blue') boxwhisker = hv.BoxWhisker(pool_ride_distance_time_year_less_hour, ['total_time', 'customer'], 'amount') plot_opts = dict(show_legend=False, width=800, height=400) I am trying to color it differently