如何使用 CSV 文件显示分组图

Question

import pandas as pd
import plotly
import plotly.express as px
import plotly.io as pio

df = pd.read_csv("final_spreadsheet.csv")

barchart = px.bar(
    data_frame = df,
    x = "Post-Lockdown Period (May - September)",
    y = "Post-Lockdown Period (May - September)",
    color = "Peak-Lockdown Period (March-May)",
    opacity = 0.9,
    orientation ="v",
    barmode = 'relative',
)
pio.show(barchart)

我希望 x 轴是不同的行为变量，对于每个行为变量，我希望有两个条形图，一个代表大流行高峰，一个代表大流行后。我也希望 y 轴只是每个的值

这是我目前的尝试，但没有出现图表。附上一张excel表格的CSV文件图片

Answer 1

在 plotly.express 中，您可以通过在参数 y 中传递要组合在一起的两个变量的列表来创建分组条形图。在您的情况下，您需要将参数y = ['Peak-Lockdown Period (March-May)','Post-Lockdown Period (May-September)'] 以及参数barmode = 'grouped' 传递给px.bar。我创建了一个示例 DataFrame 来说明：

import pandas as pd
import plotly.express as px
import plotly.io as pio

# df = pd.read_csv("final_spreadsheet.csv")

## create example DataFrame similar to yours
df = pd.DataFrame({
    'Behavioral': list('ABCD'),
    'Peak-Lockdown Period (March-May)': [76.7,26.12,0,2.94],
    'Post-Lockdown Period (May-September)': [77.32,26.38,0,3.36]
})


barchart = px.bar(
    data_frame = df,
    x = 'Behavioral',
    y = ['Peak-Lockdown Period (March-May)','Post-Lockdown Period (May-September)'],
    # color = "Peak-Lockdown Period (March-May)",
    opacity = 0.9,
    orientation ="v",
    barmode = 'group',
)

pio.show(barchart)

编辑：您可以使用 plotly.graph_objects 完成同样的事情：

import plotly.graph_objects as go

fig = go.Figure(data=[
    go.Bar(name='Peak-Lockdown Period (March-May)', x=df['Behavioral'].values, y=df['Peak-Lockdown Period (March-May)'].values),
    go.Bar(name='Post-Lockdown Period (May-September)', x=df['Behavioral'].values, y=df['Post-Lockdown Period (May-September)'].values),
])