Question

我有一张burn缩的图表,显示轴和轴上其余物体的日期。有时,我拥有大量的“停滞”数据(X-amount时间未完成任何物体)。停滞的数据正在超强,观众对线图的终端部分更感兴趣。鉴于两个已知日期,是否有办法压缩一系列轴心日期?

有了更多的数据,但这里是一个快速可再生的例子(也使用上游)。

import datetime
import streamlit as st
import altair as alt
import pandas as pd

x_values = [datetime.date(2022, 1, 7), datetime.date(2022, 1, 28), datetime.date(2022, 1, 29), datetime.date(2022, 1, 30), datetime.date(2022, 1, 31), datetime.date(2022, 2, 1), datetime.date(2022, 2, 2), datetime.date(2022, 2, 3), datetime.date(2022, 2, 4), datetime.date(2022, 2, 5), datetime.date(2022, 2, 6), datetime.date(2022, 2, 7), datetime.date(2022, 2, 8), datetime.date(2022, 2, 9), datetime.date(2022, 2, 10), datetime.date(2022, 2, 11), datetime.date(2022, 2, 12),datetime.date(2022, 12, 8), datetime.date(2023, 8, 20), datetime.date(2023, 8, 21), datetime.date(2023, 8, 22), datetime.date(2023, 8, 23), datetime.date(2023, 8, 24), datetime.date(2023, 8, 25), datetime.date(2023, 8, 26), datetime.date(2023, 8, 27), datetime.date(2023, 8, 28), datetime.date(2023, 8, 29), datetime.date(2023, 8, 30), datetime.date(2023, 8, 31), datetime.date(2023, 9, 1), datetime.date(2023, 9, 2), datetime.date(2023, 9, 3), datetime.date(2023, 9, 4), datetime.date(2023, 9, 5), datetime.date(2023, 9, 6), datetime.date(2023, 9, 7), datetime.date(2023, 9, 8), datetime.date(2023, 9, 9)]

y_values = [3521, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 1808.695652173913, 1417.391304347826, 1417.391304347826, 1417.391304347826, 1026.086956521739, 634.782608695652, 243.47826086956502, 0]

# Burndown line graph
line_data = pd.DataFrame({ x : x_values,  y : y_values})

chart_width = 400
chart_height = 600

line_chart = alt.Chart(line_data).mark_line().encode(
    x=alt.X( x:T , axis=alt.Axis(title= Date , grid=True, ticks=True, tickCount=12,
                                    format= %Y-%m-%d , labelAngle=-45, tickColor= pink , tickSize=10, tickWidth=3)),

    y=alt.Y( y:Q , axis=alt.Axis(title= Tiles ))
)
st.altair_chart(line_chart, use_container_width=True)

Answer 1

It s a bit hacky, but you can create two separate charts side by side by filtering the data before and after the known dates. For the right chart, we can set the domain of the yaxis to be the same as the left chart, then remove the title and ticks from the y-axis to clean up the appearance.

import datetime
import streamlit as st
import altair as alt
import pandas as pd

x_values = [datetime.date(2022, 1, 7), datetime.date(2022, 1, 28), datetime.date(2022, 1, 29), datetime.date(2022, 1, 30), datetime.date(2022, 1, 31), datetime.date(2022, 2, 1), datetime.date(2022, 2, 2), datetime.date(2022, 2, 3), datetime.date(2022, 2, 4), datetime.date(2022, 2, 5), datetime.date(2022, 2, 6), datetime.date(2022, 2, 7), datetime.date(2022, 2, 8), datetime.date(2022, 2, 9), datetime.date(2022, 2, 10), datetime.date(2022, 2, 11), datetime.date(2022, 2, 12),datetime.date(2022, 12, 8), datetime.date(2023, 8, 20), datetime.date(2023, 8, 21), datetime.date(2023, 8, 22), datetime.date(2023, 8, 23), datetime.date(2023, 8, 24), datetime.date(2023, 8, 25), datetime.date(2023, 8, 26), datetime.date(2023, 8, 27), datetime.date(2023, 8, 28), datetime.date(2023, 8, 29), datetime.date(2023, 8, 30), datetime.date(2023, 8, 31), datetime.date(2023, 9, 1), datetime.date(2023, 9, 2), datetime.date(2023, 9, 3), datetime.date(2023, 9, 4), datetime.date(2023, 9, 5), datetime.date(2023, 9, 6), datetime.date(2023, 9, 7), datetime.date(2023, 9, 8), datetime.date(2023, 9, 9)]

y_values = [3521, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 2200, 1808.695652173913, 1417.391304347826, 1417.391304347826, 1417.391304347826, 1026.086956521739, 634.782608695652, 243.47826086956502, 0]

# Burndown line graph
line_data = pd.DataFrame({ x : x_values,  y : y_values})

chart_width = 400
chart_height = 600

known_date_1 = datetime.date(2022, 2, 1)
known_date_2 = datetime.date(2023, 8, 20)

line_data_1 = line_data[line_data[ x ] <= known_date_1]
line_data_2 = line_data[line_data[ x ] >= known_date_2]

line_chart_1 = alt.Chart(line_data_1).mark_line().encode(
    x=alt.X( x:T , axis=alt.Axis(title= Date , grid=True, ticks=True, tickCount=12,
                                    format= %Y-%m-%d , labelAngle=-45, tickColor= pink , tickSize=10, tickWidth=3)),

    y=alt.Y( y:Q , axis=alt.Axis(title= Tiles ))
)

line_chart_2 = alt.Chart(line_data_2).mark_line().encode(
    x=alt.X( x:T , axis=alt.Axis(title=None, grid=True, ticks=True, tickCount=12,
                                    format= %Y-%m-%d , labelAngle=-45, tickColor= pink , tickSize=10, tickWidth=3)),

    y=alt.Y( y:Q , axis=alt.Axis(title=None, labels=False), scale=alt.Scale(domain=[0, 4000]))
)

full_chart = alt.hconcat(line_chart_1, line_chart_2)

st.altair_chart(full_chart, use_container_width=True)

友情链接