Develop Reference

Python Plotly multiple charts in one single view

I want use a for cycle to call a charting function and then represent the outcome chart into a section of a multi charting pageExample single chart
expected outcome
I have a charting function (see below Charting Function Section) that i recall in a the main script with a for cycle to get several charts in sequence. Now I would like to represent all the charts, in compact size (2 columns 4 rows) in one single page. In literature I find that Subplot allows me to do so but I struggle to find the right command to represent the outcome from the charting function.
I thought something like the below in the Main Section would work but it is not
---------- Main Section ---------
import pandas as pd
import numpy as np
import plotly.graph_objs as go
from sklearn.cluster import KMeans
from plotly.subplots import make_subplots
for cont in range(8):
fig = charting_func(cont)
fig_all.add_trace(fig,
row=1, col=1
) #row and col incrementing function to be defined
fig_all.update_layout(height=600, width=800, title_text="Side By Side Subplots")
fig_all.show()
----- Charting Function ------
def charting_func(n_chrt):
# Arbitrarily 10 colors for up to 10 clusters
#colors = ['red', 'orange', 'yellow', 'green', 'blue', 'indigo', 'violet', 'purple','pink', 'silver']
# Create Scatter plot, assigning each point a color where
# point group = color index.
fig = btc.plot.scatter(
x=btc.index,
y="Adj Close",
color=[colors[i] for i in lists_clusters[n_chrt]],
title="k-values = {0}".format(n_chrt+2)
)
# Add horizontal lines
for cluster_avg in output[n_chrt][1:-1]:
fig.add_hline(y=cluster_avg, line_width=1, line_color="blue")
# Add a trace of the price for better clarity
fig.add_trace(go.Scatter(
x=btc.index,
y=btc['Adj Close'],
line_color="black",
line_width=1
))
# Make it pretty
layout = go.Layout(
plot_bgcolor='#D9D9D9',
showlegend=False,
# Font Families
font_family='Monospace',
font_color='#000000',
font_size=20,
xaxis=dict(
rangeslider=dict(
visible=False
))
)
fig.update_layout(layout)
return fig
type here

The basic form of a subplot is to add a location arrangement to the graph setup. So the functionalization needs to have matrix information or something like that. I have no data to present, so I have taken the stock prices of 4 companies and graphed them. As for the clustering by price, it is not included in the code, so the binning process is used to get the values and labels for the horizontal line. Please rewrite this part to your own logic. If you are good enough, the functionalization should work well.
import pandas as pd
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import itertools
import yfinance as yf
stock = ['TSLA','MSFT','AAPL','AMD']
#fig = go.Figure()
fig = make_subplots(rows=2, cols=2, subplot_titles=['MSFT','TSLA','AMD','AAPL'])
for s,rc in zip(stock, itertools.product([1,2],[2,1])):
#print(s, rc[0], rc[1])
df = yf.download(s, start="2017-09-01", end="2022-04-01", interval='1mo', progress=False)
colors = ['blue', 'red', 'green', 'purple', 'orange']
s_cut, bins = pd.cut(df['Adj Close'], 5, retbins=True, labels=colors)
fig.add_trace(go.Scatter(mode='markers+lines',
x=df.index,
y=df['Adj Close'],
marker=dict(
size=10,
color=s_cut.tolist()
)),
row=rc[0], col=rc[1]
)
for b in bins[1:-1]:
fig.add_hline(y=b, line_width=1, line_color="blue", row=rc[0], col=rc[1])
fig.update_layout(autosize=True, height=600, title_text="Side By Side Subplots")
fig.show()

Use one color for multiple traces added to a Figure using Plotly

I have started from the following example:
from plotly.subplots import make_subplots
from plotly import graph_objects as go
fig = make_subplots(rows=3, cols=1, subplot_titles=["foo", "bar", "goo"])
for i in range(3):
fig.add_trace(go.Box(x=list(range(100)), boxmean="sd", showlegend=False), row=i + 1, col=1)
fig.update_layout(height=600, width=1200, title_text="Yo Yo")
fig
It yields three box plots in three rows of a subplots Plotly container:
My objective is:
Get rid of the trace X strings on the left.
Use the same color for all three subplots.
By using:
fig.add_trace(go.Box(x=list(range(100)), boxmean="sd", showlegend=False, fillcolor="blue"), row=i + 1, col=1)
I'm getting closer to the second objective, but it is not yet there:
I'm guessing I can ask for a color cycle consisting of a single color; but I didn't manage to do that.

We have already tried the fill and obtained results, so I think the remaining task is to align the line colors. The y-axis labels can be set to empty by name. There are other ways to do this, but I think this is the easiest.
from plotly.subplots import make_subplots
from plotly import graph_objects as go
fig = make_subplots(rows=3, cols=1, subplot_titles=["foo", "bar", "goo"])
for i in range(3):
fig.add_trace(go.Box(x=list(range(100)),
boxmean="sd",
fillcolor='blue',
line={'color':'red'},
name='',
showlegend=False), row=i + 1, col=1)
fig.update_layout(height=600, width=1200, title_text="Yo Yo")
fig.show()

How to specify the x coordinate on a grouped bar chart on plotly?

I made a bar chart with python plotly, and I want to put a marker on a particular bar, example non-smoking females.
Does anyone know how to specify this?
I took an example from the plotly documentation, if I try to put the marker it just takes the center of the main category.
import plotly.express as px
df = px.data.tips()
fig = px.histogram(df, x="sex", y="total_bill",
color='smoker', barmode='group',
height=400)
#trying to set the marker
fig.add_trace(
go.Scatter(x=["Female"],
y=[1100]
))
fig.show()

inspired by this: https://community.plotly.com/t/grouped-bar-charts-with-corresponding-line-chart/19562/4
use xaxis2, work out position, have hardcoded it, but 0.15 has relationship to number of traces in bargoup and x value
import plotly.express as px
import plotly.graph_objects as go
import numpy as np
df = px.data.tips()
fig = px.histogram(
df, x="sex", y="total_bill", color="smoker", barmode="group", height=400
)
# trying to set the marker
fig.add_trace(
go.Scatter(
x=[0.15],
y=[1100],
customdata=[["No", "Female"]],
xaxis="x2",
hovertemplate="smoker=%{customdata[0]}<br>sex=%{customdata[1]}<br>sum of total_bill=%{y}<extra></extra>",
)
)
fig.update_layout(xaxis2={"overlaying": "x", "range": [0, 1], "showticklabels": False})
fig

How to change Plotly Wind rose polar axis?

I created a Plotly windrose and wanted to change the inner circle limits to some other values(to get the same circle limit as my other wind roses). Here I want to change inner circle size to 0,2,4,6,8,10 to 0,2.5,5,7.5,10. Here is my code and my current windrose is already attached.
import plotly.express as px
df = px.data.wind()
fig = px.bar_polar(df, r="frequency", theta="direction",
color="strength", template="plotly_dark",
color_discrete_sequence=px.colors.sequential.Plasma_r)
fig.show()

This is not well documented but it has a similar behaviour of tickmode--array.
import plotly.express as px
df = px.data.wind()
fig = px.bar_polar(df, r="frequency", theta="direction",
color="strength", template="plotly_dark",
color_discrete_sequence= px.colors.sequential.Plasma_r)
fig.update_layout(
polar=dict(
radialaxis=dict(tickvals = [0, 2.5, 5, 7.5, 10])
)
)
fig.show()

Plotly: How to set line color?

How can I set the color of a line in plotly?
import plotly.graph_objects as go
from plotly.subplots import make_subplots
fig = make_subplots(rows=2, cols=1, subplot_titles=('Plot 1', 'Plot 2'))
# plot the first line of the first plot
fig.append_trace(go.Scatter(x=self.x_axis_pd, y=self.y_1, mode='lines+markers', name='line#1'), row=1, col=1) # this line should be #ffe476
I tried fillcolor but that I suspected doesn't work because this is a simple line.

You can add line=dict(color="#ffe476") inside your go.Scatter(...) call. Documentation here: https://plot.ly/python/reference/#scatter-line-color

#nicolaskruchten is of course right, but I'd like to throw in two other options:
line_color="#0000ff"
And:
fig['data'][0]['line']['color']="#00ff00"
Or:
fig.data[0].line.color = "#00ff00"
I particularly appreciate the flexibility of the latter option since it easily lets you set a new color for a desired line after you've built a figure using for example fig.append_trace(go.Scatter()) or fig = go.Figure(data=go.Scatter)). Below is an example using all three options.
Code 1:
import plotly.graph_objects as go
import numpy as np
t = np.linspace(0, 10, 100)
y = np.cos(t)
y2= np.sin(t)
fig = go.Figure(data=go.Scatter(x=t, y=y,mode='lines+markers', line_color='#ffe476'))
fig.add_trace(go.Scatter(x=t, y=y2,mode='lines+markers', line=dict(color="#0000ff")))
fig.show()
Plot 1:
Now you can change the colors directly if you insert the snippet below in a new cell and run it.
Code 2:
fig['data'][0]['line']['color']="#00ff00"
fig.show()
Plot 2:

fig.add_trace(
go.Scatter(
x=list(dict_val['yolo_timecost'].keys()),
y=signal.savgol_filter(list(dict_val['yolo_timecost'].values()),2653,3),
mode='lines',
name='YOLOv3实时耗时',
line=dict(
color='rgb(204, 204, 204)',
width=5
),
),
)

fig.data[0].line.color = 'rgb(204, 20, 204)'

You can use color_discrete_sequence like that
import plotly.express as px
df = px.data.gapminder().query("country=='Canada'")
fig = px.line(df, x="year", y="lifeExp", title='Life expectancy in Canada',color_discrete_sequence=["#ff97ff"])
fig.show()