I want to change the variable/label names in plotly express in python. I first create a plot:
import pandas as pd
import plotly.express as px
d = {'col1': [1, 2, 3], 'col2': [3, 4, 5]}
df = pd.DataFrame(data=d)
fig = px.line(df, x=df.index, y=['col1', 'col2'])
fig.show()
Which yields:
I want to change the label names from col1 to hello and from col2 to hi. I have tried using labels in the figure, but I cannot get it to work:
fig = px.line(df, x=df.index, y=['col1', 'col2'], labels={'col1': "hello", 'col2': "hi"})
fig.show()
But this seems to do nothing, while not producing an error. Obviously I could achieve my goals by changing the column names, but the actual plot i'm trying to create doesn't really allow for that since it comes from several different dataframes.
So I would add legendgroup = newnames[t.name] and hovertemplate = t. hovertemplate. replace(t.name, newnames[t.name]) into the mix.
As a general rule, there are two ways to add text labels to figures: Certain trace types, notably in the scatter family (e.g. scatter , scatter3d , scattergeo etc), support a text attribute, and can be displayed with or without markers. Standalone text annotations can be added to figures using fig.
Plotly Show Legend To disable the Legend, we can use the update_layout() function and set the showlegend parameter to false.
Using Plotly, it is easy to create a Dashboard. The difference from the Plotly Express is that you will have to use plotly. graph_objects as go instead of plotly express. The gist below in my GitHub has the entire code that you can use as a template to create your own visualizations.
Without changing the data source, a complete replacement of names both in the legend, legendgroup and hovertemplate will require:
newnames = {'col1':'hello', 'col2': 'hi'}
fig.for_each_trace(lambda t: t.update(name = newnames[t.name],
legendgroup = newnames[t.name],
hovertemplate = t.hovertemplate.replace(t.name, newnames[t.name])
)
)
Using
fig.for_each_trace(lambda t: t.update(name = newnames[t.name]))
...you can change the names in the legend without ghanging the source by using a dict
newnames = {'col1':'hello', 'col2': 'hi'}
...and map new names to the existing col1
and col2
in the following part of the figure structure (for your first trace, col1
):
{'hovertemplate': 'variable=col1<br>index=%{x}<br>value=%{y}<extra></extra>',
'legendgroup': 'col1',
'line': {'color': '#636efa', 'dash': 'solid'},
'mode': 'lines',
'name': 'hello', # <============================= here!
'orientation': 'v',
'showlegend': True,
'type': 'scatter',
'x': array([0, 1, 2], dtype=int64),
'xaxis': 'x',
'y': array([1, 2, 3], dtype=int64),
'yaxis': 'y'},
But as you can see, this doesn't do anything with 'legendgroup': 'col1'
, nor 'hovertemplate': 'variable=col1<br>index=%{x}<br>value=%{y}<extra></extra>'
And depending on the complexity of your figure, this can pose a problem. So I would add legendgroup = newnames[t.name]
and hovertemplate = t.hovertemplate.replace(t.name, newnames[t.name])
into the mix.
import pandas as pd
import plotly.express as px
from itertools import cycle
d = {'col1': [1, 2, 3], 'col2': [3, 4, 5]}
df = pd.DataFrame(data=d)
fig = px.line(df, x=df.index, y=['col1', 'col2'])
newnames = {'col1':'hello', 'col2': 'hi'}
fig.for_each_trace(lambda t: t.update(name = newnames[t.name],
legendgroup = newnames[t.name],
hovertemplate = t.hovertemplate.replace(t.name, newnames[t.name])
)
)
Add the "name" parameter: go.Scatter(name=...)
Source https://plotly.com/python/figure-labels/
fig = go.Figure()
fig.add_trace(go.Scatter(
x=[0, 1, 2, 3, 4, 5, 6, 7, 8],
y=[0, 1, 2, 3, 4, 5, 6, 7, 8],
name="Name of Trace 1" # this sets its legend entry
))
fig.add_trace(go.Scatter(
x=[0, 1, 2, 3, 4, 5, 6, 7, 8],
y=[1, 0, 3, 2, 5, 4, 7, 6, 8],
name="Name of Trace 2"
))
fig.update_layout(
title="Plot Title",
xaxis_title="X Axis Title",
yaxis_title="X Axis Title",
legend_title="Legend Title",
font=dict(
family="Courier New, monospace",
size=18,
color="RebeccaPurple"
)
)
fig.show()
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