66 extension : .md
77 format_name : markdown
88 format_version : ' 1.2'
9- jupytext_version : 1.3.1
9+ jupytext_version : 1.4.2
1010 kernelspec :
1111 display_name : Python 3
1212 language : python
@@ -20,7 +20,7 @@ jupyter:
2020 name : python
2121 nbconvert_exporter : python
2222 pygments_lexer : ipython3
23- version : 3.6.8
23+ version : 3.7.7
2424 plotly :
2525 description : How to plot date and time in python.
2626 display_as : financial
@@ -207,7 +207,7 @@ import pandas as pd
207207df = pd.read_csv(' https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv' )
208208
209209fig = px.scatter(df, x = ' Date' , y = ' AAPL.High' , range_x = [' 2015-12-01' , ' 2016-01-15' ],
210- title = " Hide Gaps with rangebreaks" )
210+ title = " Hide Weekend and Holiday Gaps with rangebreaks" )
211211fig.update_xaxes(
212212 rangebreaks = [
213213 dict (bounds = [" sat" , " mon" ]), # hide weekends
@@ -216,3 +216,48 @@ fig.update_xaxes(
216216)
217217fig.show()
218218```
219+
220+ ### Hiding Non-Business Hours
221+
222+ The ` rangebreaks ` feature described above works for hiding hourly periods as well.
223+
224+ ``` python
225+ import plotly.express as px
226+ import pandas as pd
227+ import numpy as np
228+ np.random.seed(1 )
229+
230+ work_week_40h = pd.date_range(start = ' 2020-03-01' , end = ' 2020-03-07' , freq = " BH" )
231+
232+ df = pd.DataFrame(dict (
233+ date = work_week_40h,
234+ value = np.cumsum(np.random.rand(40 )- 0.5 )
235+ ))
236+
237+ fig = px.scatter(df, x = " date" , y = " value" ,
238+ title = " Default Display with Gaps" )
239+ fig.show()
240+ ```
241+
242+ ``` python
243+ import plotly.express as px
244+ import pandas as pd
245+ import numpy as np
246+ np.random.seed(1 )
247+
248+ work_week_40h = pd.date_range(start = ' 2020-03-01' , end = ' 2020-03-07' , freq = " BH" )
249+
250+ df = pd.DataFrame(dict (
251+ date = work_week_40h,
252+ value = np.cumsum(np.random.rand(40 )- 0.5 )
253+ ))
254+
255+ fig = px.scatter(df, x = " date" , y = " value" ,
256+ title = " Hide Non-Business Hour Gaps with rangebreaks" )
257+ fig.update_xaxes(
258+ rangebreaks = [
259+ dict (bounds = [17 , 9 ], pattern = " hour" ), # hide hours outside of 9am-5pm
260+ ]
261+ )
262+ fig.show()
263+ ```
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