Plotly 条形图 - 根据正值/负值更改颜色 - python

Question

I have the following code which plots a bar chart (1 series), but I need the bars to be coloured blue if the 'Net' value is positive, and red if its negative:

import pandas as pd
import plotly.graph_objects as go

df = pd.DataFrame({
     'Net':[15,20,-10,-15], 
     'Date':['07/14/2020','07/15/2020','07/16/2020','07/17/2020']
})

df['Date'] = pd.to_datetime(df['Date'])
fig = go.Figure(data=[go.Bar(name='Net', x=df['Date'], y=df['Net'])])
fig.update_layout(barmode='stack')
fig.show()

Answer 1

You can check documentation here . Full code as following

import pandas as pd
import plotly.graph_objects as go
import numpy as np

# Data

df = pd.DataFrame({
     'Net':[15,20,-10,-15], 
     'Date':['07/14/2020','07/15/2020','07/16/2020','07/17/2020']
})

df['Date'] = pd.to_datetime(df['Date'])

## here I'm adding a column with colors
df["Color"] = np.where(df["Net"]<0, 'red', 'green')

# Plot
fig = go.Figure()
fig.add_trace(
    go.Bar(name='Net',
           x=df['Date'],
           y=df['Net'],
           marker_color=df['Color']))
fig.update_layout(barmode='stack')
fig.show()

Answer 2

@rpanai that is a great answer and got me where I needed to go. I wanted to simply add a way to do the same if using plotly.express .

Note that most of this is the same as above.

import pandas as pd
import numpy as np
import plotly.express as px

df = pd.DataFrame({
       'Net':[15,20,-10,-15],
       'Date':['07/14/2020','07/15/2020','07/16/2020','07/17/2020']
})
df['Date'] = pd.to_datetime(df['Date'])
df["Color"] = np.where(df["Net"]<0, 'red', 'green')

# PLOT
fig = px.bar(df,x="Date",y="Net")

# COLOR
fig.update_traces(marker_color=df["Color"])

fig.show()