As shown below I used the example code of the Bokeh library. I tried add the hovertool and edit the output of the hovertool, but there are only "???" shown.
Can anybody give me a tip, to add and configure the hover tool in the example code?
import pandas as pd
from bokeh.palettes import Spectral4
from bokeh.plotting import figure, output_file, show
from bokeh.sampledata.stocks import AAPL, IBM, MSFT, GOOG
p = figure(plot_width=800, plot_height=250, x_axis_type="datetime")
p.title.text = 'Click on legend entries to hide the corresponding lines'
for data, name, color in zip([AAPL, IBM, MSFT, GOOG], ["AAPL", "IBM", "MSFT", "GOOG"], Spectral4):
df = pd.DataFrame(data)
df['date'] = pd.to_datetime(df['date'])
p.line(df['date'], df['close'], line_width=2, color=color, alpha=0.8, legend=name)
p.legend.location = "top_left"
p.legend.click_policy="hide"
output_file("interactive_legend.html", title="interactive_legend.py example")
show(p)
Related
I was consulting the bokeh user guide (link) on creating interactive legends (see subsection on "Hiding glyphs").
The code given allows me to create up to 4 stacked line charts. For example, if I try to create a fifth line chart ("AAP"):
p = figure(width=800, height=250, x_axis_type="datetime")
p.title.text = 'Click on legend entries to hide the corresponding lines'
import pandas as pd
from bokeh.palettes import Spectral4
from bokeh.plotting import figure, show
from bokeh.sampledata.stocks import AAPL, GOOG, IBM, MSFT
for data, name, color in zip([AAPL, GOOG, IBM, MSFT, AAPL], ["AAPL", "GOOG", "IBM", "MSFT", "AAP"], Spectral4):
df = pd.DataFrame(data)
df['date'] = pd.to_datetime(df['date'])
p.line(df['date'], df['close'], line_width=2, color=color, alpha=0.8, legend_label=name)
p.legend.location = "top_left"
p.legend.click_policy="hide"
show(p)
it will still only show four.
I was wondering if it is possible to extend this code and create many more line charts (say 20) and if so, how this can be done.
Thank you
Your approach is working fine and would work, if you use Spectral5 instead of Spectral4 as palette. You have to know, that zip iterates over all lists and stops if one list has no more items. That was the case.
Minimal working example:
import pandas as pd
from bokeh.plotting import figure, show, output_notebook
from bokeh.sampledata.stocks import AAPL, GOOG, IBM, MSFT
output_notebook()
p = figure(width=800, height=250, x_axis_type="datetime")
p.title.text = 'Click on legend entries to hide the corresponding lines'
dataset = [AAPL, GOOG, IBM, MSFT, AAPL]
nameset = ["AAPL", "GOOG", "IBM", "MSFT", "AAP"]
colorset = ['blue', 'red', 'green', 'magenta', 'black']
for data, name, color in zip(dataset, nameset, colorset):
df = pd.DataFrame(data)
df['date'] = pd.to_datetime(df['date'])
p.line(df['date'], df['close'], line_width=2, color=color, alpha=0.8, legend_label=name)
p.legend.location = "top_left"
p.legend.click_policy="hide"
show(p)
Output:
Comment
For this I used bokeh 2.4.3 but with bokeh 3.+ this should work, too.
I'm trying to highlight last value of a time series plot by plot its value on yaxis, as shown in this question. I prefer using LabelSet over Legend because you can precisely control the text positions and also using a data source to update it. But unfortunately, I can not find out how to draw label text outside the plot box.
Here is some code to plot LabelSet and notice how the text is only shown inside the box (66.1x is partially blocked by yaxis):
import pandas as pd
from bokeh.io import output_notebook
output_notebook()
from bokeh.plotting import figure, show
from bokeh.models import LabelSet, ColumnDataSource
#import bokeh.sampledata
#bokeh.sampledata.download()
from bokeh.sampledata.stocks import MSFT
df = pd.DataFrame(MSFT)[:50]
df["date"] = pd.to_datetime(df["date"])
p = figure(
x_axis_type="datetime", width=1000, toolbar_location='left',
title = "MSFT Candlestick", y_axis_location="right")
p.line(df.date, df.close)
ds = ColumnDataSource({'x': [df.date.iloc[-1]], 'y': [df.close.iloc[-1]], 'text': [' ' + str(df.close.iloc[-1])]})
ls = LabelSet(x='x', y='y', text='text', source=ds)
p.add_layout(ls)
show(p)
Please let me know how to show LabelSet outside the box, Thanks
I just discovered Bokeh recently, and I try to display a legend for each day of week (represented by 'startdate_dayweek'). The legend should contain the color for each row corresponding to each day.
import pandas as pd
from bokeh.plotting import figure, show
from bokeh.io import output_file
from bokeh.palettes import Set1_7
output_file("conso_daily.html")
treatcriteria_data_global = pd.read_csv(r"treatcriteria_evolution.csv", sep=';')
final_global_data = treatcriteria_data_global.groupby(['startdate_weekyear','startdate_dayweek'],as_index = False).sum().pivot('startdate_weekyear','startdate_dayweek').fillna(0)
numlines = len(final_global_data.columns)
palette = Set1_7[0:numlines]
ts_list_of_list = []
for i in range(0,len(final_global_data.columns)):
ts_list_of_list.append(final_global_data.index)
vals_list_of_list = final_global_data.values.T.tolist()
p = figure(width=500, height=300)
p.left[0].formatter.use_scientific = False
p.multi_line(ts_list_of_list, vals_list_of_list,
legend='startdate_dayweek',
line_color = palette,
line_width=4)
show(p)
But I don't have the expected result in the legend:
How to have the legend for each day? Is the problem due to the fact that I created a MultiIndex table? Thanks.
The multi_line() function can take the parameter legend_field or legend_group. Both are working very well for your usecase, if you use a ColumnDataSource as source. Keep in mind, that a error will come if you use both parameters at the same time.
Minimal Example
from bokeh.plotting import figure, show, output_notebook
from bokeh.models import ColumnDataSource
output_notebook()
source = ColumnDataSource(dict(
xs=[[1,2,3,4,5],[1,2,3,4,5],[1,2,3,4,5]],
ys=[[1,2,3,4,5],[1,1,1,1,5],[5,4,3,2,1]],
legend =['red', 'green', 'blue'],
line_color = ['red', 'green', 'blue']))
p = figure(width=500, height=300)
p.multi_line(xs='xs',
ys='ys',
legend_field ='legend',
line_color = 'line_color',
source=source,
line_width=4)
show(p)
Output
I have a dataframe that details sales of various product categories vs. time. I'd like to make a "line and marker" plot of sales vs. time, per category. To my surprise, this appears to be very difficult in Bokeh.
The scatter plot is easy. But then trying to overplot a line of sales vs. date with the same source (so I can update both scatter and line plots in one go when the source updates) and in such a way that the colors of the line match the colors of the scatter plot markers proves near impossible.
Minimal reproducible example with contrived data:
import pandas as pd
df = pd.DataFrame({'Date':['2020-01-01','2020-01-02','2020-01-01','2020-01-02'],\
'Product Category':['shoes','shoes','grocery','grocery'],\
'Sales':[100,180,21,22],'Colors':['red','red','green','green']})
df['Date'] = pd.to_datetime(df['Date'])
from bokeh.io import output_notebook
output_notebook()
from bokeh.io import output_file, show
from bokeh.plotting import figure
source = ColumnDataSource(df)
plot = figure(x_axis_type="datetime", plot_width=800, toolbar_location=None)
plot.scatter(x="Date",y="Sales",size=15, source=source, fill_color="Colors", fill_alpha=0.5, \
line_color="Colors",legend="Product Category")
for cat in list(set(source.data['Product Category'])):
tmp = source.to_df()
col = tmp[tmp['Product Category']==cat]['Colors'].values[0]
plot.line(x="Date",y="Sales",source=source, line_color=col)
show(plot)
Here's what it looks like, which is clearly wrong:
Here's what I want and don't know how to make:
Can Bokeh not make such plots, where scatter markers and lines have the same color per category, with a legend?
With bokeh it is often helpful to first think about the visualisation you want and then structuring the data source appropriately. You want two lines, on per category, the x axis is time and y axis is the sales. Then a natural way to structure your data source is the following:
df = pd.DataFrame({'Date':['2020-01-01','2020-01-02'],
'Shoe Sales':[100, 180],
'Grocery Sales': [21, 22]
})
from bokeh.io import output_notebook
output_notebook()
from bokeh.io import output_file, show
from bokeh.plotting import figure
source = ColumnDataSource(df)
plot = figure(x_axis_type="datetime", plot_width=800, toolbar_location=None)
categories = ["Shoe Sales", "Grocery Sales"]
colors = {"Shoe Sales": "red", "Grocery Sales": "green"}
for category in categories:
plot.scatter(x="Date",y=category,size=15, source=source, fill_color=colors[category], legend=category)
plot.line(x="Date",y=category,source=source, line_color=colors[category])
show(plot)
The solutions is to group your data. Then you can plot lines for each group.
Minimal Example
import pandas as pd
from bokeh.plotting import figure, show, output_notebook
output_notebook()
df = pd.DataFrame({'Date':['2020-01-01','2020-01-02','2020-01-01','2020-01-02'],
'Product Category':['shoes','shoes','grocery','grocery'],
'Sales':[100,180,21,22],'Colors':['red','red','green','green']})
df['Date'] = pd.to_datetime(df['Date'])
plot = figure(x_axis_type="datetime",
plot_width=400,
plot_height=400,
toolbar_location=None
)
plot.scatter(x="Date",
y="Sales",
size=15,
source=df,
fill_color="Colors",
fill_alpha=0.5,
line_color="Colors",
legend_field="Product Category"
)
for color in df['Colors'].unique():
plot.line(x="Date", y="Sales", source=df[df['Colors']==color], line_color=color)
show(plot)
Output
I want to draw a circle with bokeh, the color of this circle depends on a column of DataFrame. But I got an empty plot. If i don't specify a color argument for p.circle, it'll work fine.
Here is the code, you can copy and paste and run it.
from bokeh.plotting import figure, output_file, show
from bokeh.models import ColumnDataSource, CategoricalColorMapper
from bokeh.palettes import Spectral11
import pandas as pd
df = pd.DataFrame({
'price':[10,15,20,25,30],
'action':[0,1,0,2,3],
'sign':[0,-1,0,1,-1]
})
source = ColumnDataSource(data=dict(
index=df.index,
price=df.price,
action=df.action,
sign=df.sign
))
color_mapper = CategoricalColorMapper(factors= [str(i) for i in list(df.sign.unique())], palette=Spectral11)
p = figure(plot_width=800, plot_height=400)
# this works fine
p.circle('index', 'price', radius=0.2 , source=source)
# this don't work
p.circle('index', 'price', radius=0.2 , color={'field':'sign', 'transform':color_mapper}, source=source)
show(p)
Bokeh doesn't like it when you take some information from a ColumnDataSource, and other information from a different source. This worked for me(in a notebook):
from bokeh.plotting import figure, output_notebook, show
from bokeh.models import ColumnDataSource, CategoricalColorMapper
from bokeh.palettes import Spectral11
import pandas as pd
output_notebook()
df = pd.DataFrame({
'price':[10,15,20,25,30],
'action':[0,1,0,2,3],
'sign':[0,-1,0,1,-1],
})
source = ColumnDataSource(data=dict(
index=df.index,
price=df.price,
action=df.action,
sign=df.sign,
color=[Spectral11[i+1] for i in df.sign]
))
p = figure(plot_width=800, plot_height=400)
# this don't work
p.circle('index', 'price', radius=0.2 ,
color='color',
source=source)
show(p)