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I am using plotly. I am getting the plot. The problem is, I am using seasons as colormap. I have used 1 for fall, 2 for winter, ..,4 for summer. Now, the colomap shows these numbers and also 1.5, 2.5 etc. I want to show Names instead of numbers
My code:
import plotly.express as px
from plotly.offline import plot
import plotly
fig = px.scatter_3d(df, x=xlbl, y=ylbl, z=zlbl,
color=wlbl,opacity=0,
color_continuous_scale = plotly.colors.sequential.Viridis)
temp_name = 'Temp_plot.html'
plot(fig, filename = temp_name, auto_open=False,
image_width=1200,image_height=800)
plot(fig)
Present output:
You can modify the coloraxis by adding the following lines to your code:
cat_labels = ["Fall", "Winter", "Spring", "Summer"]
fig.update_coloraxes(colorbar=dict(ticktext=cat_labels,
tickvals=list(range(1, len(cat_labels)+1))))
Sample output with random data:
this is my first foray into Plotly. I love the ease of use compared to matplotlib and bokeh. However I'm stuck on some basic questions on how to beautify my plot. First, this is the code below (its fully functional, just copy and paste!):
import plotly.express as px
from plotly.subplots import make_subplots
import plotly as py
import pandas as pd
from plotly import tools
d = {'Mkt_cd': ['Mkt1','Mkt2','Mkt3','Mkt4','Mkt5','Mkt1','Mkt2','Mkt3','Mkt4','Mkt5'],
'Category': ['Apple','Orange','Grape','Mango','Orange','Mango','Apple','Grape','Apple','Orange'],
'CategoryKey': ['Mkt1Apple','Mkt2Orange','Mkt3Grape','Mkt4Mango','Mkt5Orange','Mkt1Mango','Mkt2Apple','Mkt3Grape','Mkt4Apple','Mkt5Orange'],
'Current': [15,9,20,10,20,8,10,21,18,14],
'Goal': [50,35,21,44,20,24,14,29,28,19]
}
dataset = pd.DataFrame(d)
grouped = dataset.groupby('Category', as_index=False).sum()
data = grouped.to_dict(orient='list')
v_cat = grouped['Category'].tolist()
v_current = grouped['Current']
v_goal = grouped['Goal']
fig1 = px.bar(dataset, x = v_current, y = v_cat, orientation = 'h',
color_discrete_sequence = ["#ff0000"],height=10)
fig2 = px.bar(dataset, x = v_goal, y = v_cat, orientation = 'h',height=15)
trace1 = fig1['data'][0]
trace2 = fig2['data'][0]
fig = make_subplots(rows = 1, cols = 1, shared_xaxes=True, shared_yaxes=True)
fig.add_trace(trace2, 1, 1)
fig.add_trace(trace1, 1, 1)
fig.update_layout(barmode = 'overlay')
fig.show()
Here is the Output:
Question1: how do I make the width of v_current (shown in red bar) smaller? As in, it should be smaller in height since this is a horizontal bar. I added the height as 10 for trace1 and 15 for trace2, but they are still showing at the same heights.
Question2: Is there a way to make the v_goal (shown in blue bar) only show it's right edge, instead of a filled out bar? Something like this:
If you noticed, I also added a line under each of the category. Is there a quick way to add this as well? Not a deal breaker, just a bonus. Other things I'm trying to do is add animation, etc but that's for some other time!
Thanks in advance for answering!
Running plotly.express wil return a plotly.graph_objs._figure.Figure object. The same goes for plotly.graph_objects running go.Figure() together with, for example, go.Bar(). So after building a figure using plotly express, you can add lines or traces through references directly to the figure, like:
fig['data'][0].width = 0.4
Which is exactly what you need to set the width of your bars. And you can easily use this in combination with plotly express:
Code 1
fig = px.bar(grouped, y='Category', x = ['Current'],
orientation = 'h', barmode='overlay', opacity = 1,
color_discrete_sequence = px.colors.qualitative.Plotly[1:])
fig['data'][0].width = 0.4
Plot 1
In order to get the bars or shapes to indicate the goal levels, you can use the approach described by DerekO, or you can use:
for i, g in enumerate(grouped.Goal):
fig.add_shape(type="rect",
x0=g+1, y0=grouped.Category[i], x1=g, y1=grouped.Category[i],
line=dict(color='#636EFA', width = 28))
Complete code:
import plotly.express as px
from plotly.subplots import make_subplots
import plotly as py
import pandas as pd
from plotly import tools
d = {'Mkt_cd': ['Mkt1','Mkt2','Mkt3','Mkt4','Mkt5','Mkt1','Mkt2','Mkt3','Mkt4','Mkt5'],
'Category': ['Apple','Orange','Grape','Mango','Orange','Mango','Apple','Grape','Apple','Orange'],
'CategoryKey': ['Mkt1Apple','Mkt2Orange','Mkt3Grape','Mkt4Mango','Mkt5Orange','Mkt1Mango','Mkt2Apple','Mkt3Grape','Mkt4Apple','Mkt5Orange'],
'Current': [15,9,20,10,20,8,10,21,18,14],
'Goal': [50,35,21,44,20,24,14,29,28,19]
}
dataset = pd.DataFrame(d)
grouped = dataset.groupby('Category', as_index=False).sum()
fig = px.bar(grouped, y='Category', x = ['Current'],
orientation = 'h', barmode='overlay', opacity = 1,
color_discrete_sequence = px.colors.qualitative.Plotly[1:])
fig['data'][0].width = 0.4
fig['data'][0].marker.line.width = 0
for i, g in enumerate(grouped.Goal):
fig.add_shape(type="rect",
x0=g+1, y0=grouped.Category[i], x1=g, y1=grouped.Category[i],
line=dict(color='#636EFA', width = 28))
f = fig.full_figure_for_development(warn=False)
fig.show()
You can use Plotly Express and then directly access the figure object as #vestland described, but personally I prefer to use graph_objects to make all of the changes in one place.
I'll also point out that since you are stacking bars in one chart, you don't need subplots. You can create a graph_object with fig = go.Figure() and add traces to get stacked bars, similar to what you already did.
For question 1, if you are using go.Bar(), you can pass a width parameter. However, this is in units of the position axis, and since your y-axis is categorical, width=1 will fill the entire category, so I have chosen width=0.25 for the red bar, and width=0.3 (slightly larger) for the blue bar since that seems like it was your intention.
For question 2, the only thing that comes to mind is a hack. Split the bars into two sections (one with height = original height - 1), and set its opacity to 0 so that it is transparent. Then place down bars of height 1 on top of the transparent bars.
If you don't want the traces to show up in the legend, you can set this individually for each bar by passing showlegend=False to fig.add_trace, or hide the legend entirely by passing showlegend=False to the fig.update_layout method.
import plotly.express as px
import plotly.graph_objects as go
# from plotly.subplots import make_subplots
import plotly as py
import pandas as pd
from plotly import tools
d = {'Mkt_cd': ['Mkt1','Mkt2','Mkt3','Mkt4','Mkt5','Mkt1','Mkt2','Mkt3','Mkt4','Mkt5'],
'Category': ['Apple','Orange','Grape','Mango','Orange','Mango','Apple','Grape','Apple','Orange'],
'CategoryKey': ['Mkt1Apple','Mkt2Orange','Mkt3Grape','Mkt4Mango','Mkt5Orange','Mkt1Mango','Mkt2Apple','Mkt3Grape','Mkt4Apple','Mkt5Orange'],
'Current': [15,9,20,10,20,8,10,21,18,14],
'Goal': [50,35,21,44,20,24,14,29,28,19]
}
dataset = pd.DataFrame(d)
grouped = dataset.groupby('Category', as_index=False).sum()
data = grouped.to_dict(orient='list')
v_cat = grouped['Category'].tolist()
v_current = grouped['Current']
v_goal = grouped['Goal']
fig = go.Figure()
## you have a categorical plot and the units for width are in position axis units
## therefore width = 1 will take up the entire allotted space
## a width value of less than 1 will be the fraction of the allotted space
fig.add_trace(go.Bar(
x=v_current,
y=v_cat,
marker_color="#ff0000",
orientation='h',
width=0.25
))
## you can show the right edge of the bar by splitting it into two bars
## with the majority of the bar being transparent (opacity set to 0)
fig.add_trace(go.Bar(
x=v_goal-1,
y=v_cat,
marker_color="#ffffff",
opacity=0,
orientation='h',
width=0.30,
))
fig.add_trace(go.Bar(
x=[1]*len(v_cat),
y=v_cat,
marker_color="#1f77b4",
orientation='h',
width=0.30,
))
fig.update_layout(barmode='relative')
fig.show()
I want to create an interactive scatter plot; so I am using the plotly.graph_objects module.
My data has two columns of about 100 points.
When I make a line plot, I have no problem.
But when I try to make a scatter plot, Jupyter seems to hang (message at the bottom says - Local Host not responding)
It takes a while for Jupyter to respond and I still have no plot.
The code I am using is:
import plotly.express as px
import plotly.graph_objects as go
fig = go.Figure()
var_list = ['cloxth1 ()','cloxth2 ()']
for item in var_list:
stripped_item = item.replace(' ()','')
fig.add_trace(go.Scatter(
x=np.linspace(0,len(df),len(df)),
y=df[item],
mode='markers',
marker={'size':1},
name = item
))
fig.update_layout(title = 'CLOXTH',
xaxis_title = 'data samples',
yaxis_title = 'mV')
fig.show()
Is there anything wrong with the way I am using go.Scatter?
I tried using px.scatter instead. It seems to work, as in I get a scatter plot. But in the plotly.express case I am unable to have a proper legend for 'cloxth1' and 'cloxth2'; also, both data sets are plotted with the same color.
How can I get around this?
A few rows from the data:
Sample Data
# read in with
df = pd.read_clipboard(sep=',', index_col=[0])
# copy to clipboard
,time(s),Filename,time_stamp,time_vector(ms),time_vector_zerobased(ms),cloxth1(),cloxth2()
0.0,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:03.8,0,0,725.9097285,725.9097285
1.001,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:04.8,1001,1001,725.9097285,725.9097285
2.001,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:05.8,2001,2001,725.9097285,725.9097285
3.002,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:06.8,3002,3002,725.9097285,725.9097285
4.0,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:07.8,4000,4000,725.9097285,725.9097285
5.002,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:08.8,5002,5002,725.9097285,725.9097285
6.002,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:09.8,6002,6002,725.9097285,725.9097285
7.001,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:10.8,7001,7001,725.9097285,725.9097285
8.003,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:11.8,8003,8003,725.9097285,725.9097285
9.002,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:12.8,9002,9002,725.9097285,725.9097285
10.0,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:13.8,10000,10000,725.9097285,725.9097285
11.005,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:14.8,11005,11005,725.9097285,725.9097285
12.0,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:15.8,12000,12000,725.9097285,725.9097285
13.001,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:16.8,13001,13001,725.9097285,725.9097285
14.003,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:17.8,14003,14003,725.9097285,725.9097285
15.0,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:18.8,15000,15000,725.9097285,725.9097285
16.002,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:19.8,16002,16002,725.9097285,725.9097285
17.0,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:20.8,17000,17000,725.9097285,725.9097285
18.0,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:21.8,18000,18000,725.9097285,725.9097285
19.003,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:22.8,19003,19003,725.9097285,725.9097285
20.001,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:23.8,20001,20001,725.9097285,725.9097285
21.0,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:24.8,21000,21000,725.9097285,725.9097285
22.005,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:25.8,22005,22005,725.9097285,725.9097285
23.0,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:26.8,23000,23000,725.9097285,725.9097285
24.002,4DRBUP1N8HB706662_Trip-Detail_2020-07-20,00-04-03.csv.zip,04:27.8,24002,24002,725.9097285,725.9097285
When I introduce gaps in between bricks in a plotly annotated heatmap, vertical black lines appear behind the bricks (visible in the gaps). The lines appear to line up with the x-axis labels. Even more oddly, if the x-axis category is numeric, the label "0" will not get a vertical line. I want the vertical lines removed. I've looked at the documentation and can't figure out what these lines are. You'll notice that there are also horizontal vertical and white lines that line up with the x- and y-axis labels. I don't mind those.
import plotly.graph_objs as go
from plotly.figure_factory import create_annotated_heatmap
import numpy as np
fig = go.Figure(create_annotated_heatmap(z = np.arange(12).reshape(3,4),
x = [0,1,2,3],
y = ['A','B','C'],
xgap = 30, ygap = 30
)
)
fig.update_layout(title = 'What are these vertical lines?')
fig.show()
This is not an issue with the standard heatmap:
fig2 = go.Figure(go.Heatmap(z = np.arange(12).reshape(3,4),
x = [0,1,2,3],
y = ['A','B','C'],
xgap = 30, ygap = 30
)
)
fig2.update_layout(title = 'No vertical lines here.')
fig2.show()
Regarding the documentation from help(create_annotated_heatmap), there is a short list of parameters that don't seem to have anything to do with it, and kwargs that go through the standard plotly Heatmap.
The line under the zero is the 'zeroline' while the other lines are the 'gridlines'. They can be removed by setting zeroline=False and showgrid=False in the figure layout.
import plotly.graph_objs as go
from plotly.figure_factory import create_annotated_heatmap
import numpy as np
fig = go.Figure(create_annotated_heatmap(z=np.arange(12).reshape(3,4),
x=[0,1,2,3],
y=['A','B','C'],
xgap=30, ygap=30))
fig.update_layout(xaxis=dict(zeroline=False, showgrid=False),
yaxis=dict(zeroline=False, showgrid=False))
fig.show()
Alternatively, you can change their color to white as in the standard heatmap.
import plotly.graph_objs as go
from plotly.figure_factory import create_annotated_heatmap
import numpy as np
fig = go.Figure(create_annotated_heatmap(z=np.arange(12).reshape(3,4),
x=[0,1,2,3],
y=['A','B','C'],
xgap=30, ygap=30))
fig.update_layout(xaxis=dict(zeroline=False, gridcolor='white'),
yaxis=dict(zeroline=False, gridcolor='white'))
fig.show()
I was trying to plot choropleth map using plotly but getting a blank output.I am not getting any map.here is my code-
input-
import plotly.plotly as py
from plotly.offline import download_plotlyjs,init_notebook_mode,plot,iplot
import plotly.graph_objs as go
init_notebook_mode(connected=True)
%matplotlib inline
data = dict(type = 'choropleth',
locations = ['AZ','CA','NY'],
locationmode = 'USA-states',
colorscale= 'Portland',
text= ['text1','text2','text3'],
z=[1.0,2.0,3.0],
colorbar = {'title':'Colorbar Title'})
layout = dict(geo = {'scope':'usa'})
choromap = go.Figure(data=[data] , layout=layout)
iplot(choromap )
output-
it is a blank screen. I am sharing my screenshot.What is the issue?
Thank you in advance
https://drive.google.com/file/d/14R6zfNxnefBoe3RFlFH2YunlTbrFzfRX/view?usp=sharing
Just double click on the white space and you will get the desired output.
This worked for me.
Thanks