Which line of this code:
# Take credit amount values into a list
young = df['Credit_amount'].loc[df['Age_Group'] == 'Young'].values.tolist()
young_adults = df['Credit_amount'].loc[df['Age_Group'] == 'Young Adults'].values.tolist()
senior = df['Credit_amount'].loc[df['Age_Group'] == 'Senior'].values.tolist()
elder_credit = df['Credit_amount'].loc[df['Age_Group'] == 'Elder'].values.tolist()
# Create the box plots by age category
young_credit = go.Box(
y = young,
name = "Young",
jitter = 0.3,
pointpos = -1.8,
boxpoints = 'all',
marker = dict(
color = 'rgb(150, 198, 109)'),
line = dict(
color = 'rgb(111, 200, 37)')
)
young_adults_credit = go.Box(
y = young_adults,
name = "Young Adults",
jitter = 0.3,
pointpos = -1.8,
boxpoints = 'all',
marker = dict(
color = 'rgb(124, 236, 212)'),
line = dict(
color = 'rgb(38, 214, 177)')
)
senior_credit = go.Box(
y = senior,
name = "Seniors",
jitter = 0.3,
pointpos = -1.8,
boxpoints = 'all',
marker = dict(
color = 'rgb(241, 93, 93)'),
line = dict(
color = 'rgb(225, 44, 44)')
)
elder_credit = go.Box(
y = elder_credit,
name = "Elders",
jitter = 0.3,
pointpos = -1.8,
boxpoints = 'all',
marker = dict(
color = 'rgb(180, 121, 72)'),
line = dict(
color = 'rgb(115, 77, 46)')
)
data = [young_credit, young_adults_credit, senior_credit, elder_credit]
layout = dict(
title="Credit Amount by Age Group Segment",
xaxis = dict(title="Age Group"),
yaxis= dict(title="Credit Amount")
)
fig = dict(data=data, layout=layout)
iplot(fig, filename="Box Plot")
concerns the fragments marked in the picture below, I would like to remove those fragments from the chart and which lines of code I have to remove to achieve this goal.
I will be really thankfull for all clear answers because I can not find line of code to remove this fragments of plot.
Thank you so much!
If you Want to totally remove the points, you should remove parameters in each go.Box:
jitter = 0.3,
pointpos = -1.8,
boxpoints = 'all'
From plot.ly/python/box-plots/: With the points argument, display underlying data points with either all points (all), outliers only (outliers, default), or none of them (False).
Plot 1: boxpoints = False
Plot 2: boxpoints = 'all'
I got the same issue and can still not find the fix. The github issue is still open which Ahmed mentioned (https://github.com/plotly/plotly.js/issues/277).
Although, you can use a visible work around. It does not fix the problem! But for the vision it is fixed.
You van marker=dict(opacity=0) which makes the points invisible. When you hover over them, they are still there.
Related
I want to keep the labels when you hover, but hide the labels from just appearing over the Sankey as text.
Here is my code:
labels = df_mapping['Name'].to_numpy().tolist() + labels
count_dict = {}
source = []
target = []
value = df_subset['Stuff'].to_numpy().tolist()
index = 0
for x in unique_broad:
count_dict[x] = len(df_mapping.loc[df_mapping['Stuff'] == x])
for key in count_dict:
for i in range(count_dict[key]):
source.append(index)
index += 1
for key in count_dict:
for i in range(count_dict[key]):
target.append(index)
index += 1
number_of_colors = len(source)
color_link = ["#"+''.join([random.choice('0123456789ABCDEF') for j in range(6)])
for i in range(number_of_colors)]
link = dict(source=source, target=target, value=value, color=color_link)
node = dict(label=labels, pad=35, thickness=10)
data = go.Sankey(link=link, node=node)
fig = go.Figure(data)
fig.update_layout(
hovermode = 'x',
title="Sankey for Stuff",
font=dict(size=8, color='white'),
paper_bgcolor='#51504f'
)
return fig
You can make the labels invisible by setting the color of the labels to rgba(0,0,0,0). This ensures that the label will remain in the hovertemplate, but not show up on the nodes.
To do this you can pass textfont=dict(color="rgba(0,0,0,0)", size=1) to go.Sankey such as in the example you used from the Plotly sankey diagram documentation:
import plotly.graph_objects as go
import urllib.request, json
url = 'https://raw.githubusercontent.com/plotly/plotly.js/master/test/image/mocks/sankey_energy.json'
response = urllib.request.urlopen(url)
data = json.loads(response.read())
# override gray link colors with 'source' colors
opacity = 0.4
# change 'magenta' to its 'rgba' value to add opacity
data['data'][0]['node']['color'] = ['rgba(255,0,255, 0.8)' if color == "magenta" else color for color in data['data'][0]['node']['color']]
data['data'][0]['link']['color'] = [data['data'][0]['node']['color'][src].replace("0.8", str(opacity))
for src in data['data'][0]['link']['source']]
fig = go.Figure(data=[go.Sankey(
textfont=dict(color="rgba(0,0,0,0)", size=1),
valueformat = ".0f",
valuesuffix = "TWh",
# Define nodes
node = dict(
pad = 15,
thickness = 15,
line = dict(color = "black", width = 0.5),
label = data['data'][0]['node']['label'],
color = data['data'][0]['node']['color']
),
# Add links
link = dict(
source = data['data'][0]['link']['source'],
target = data['data'][0]['link']['target'],
value = data['data'][0]['link']['value'],
label = data['data'][0]['link']['label'],
color = data['data'][0]['link']['color']
))])
fig.update_layout(title_text="Energy forecast for 2050<br>Source: Department of Energy & Climate Change, Tom Counsell via <a href='https://bost.ocks.org/mike/sankey/'>Mike Bostock</a>",
font_size=10)
fig.show()
You get the following:
I have the following data lists:
date = ['2019-01-01', '2019-01-18', '2019-02-03']
value1 = [6798.0, 436.0, 348.0]
value2 = [500.0, 455.0, 348.0]
From these lists I generate a line graph using the plotly library, this way:
trace_1 = go.Scatter(x = date,
y = value1,
mode = 'markers+lines',
marker_color='rgb(152, 0, .8)',
name = '1')
trace_2 = go.Scatter(x = date,
y = value2,
mode = 'markers+lines',
marker_color='rgb(0, 0, .8)',
name = '2')
data_total = [trace_1, trace_2]
fig = go.Figure(data=data_total, layout=layout)
py.iplot(fig)
The graphic is working perfectly and the lines are in different colors. However, I would like the line colors, instead of manual as I did, to be automatically generated randomly.
Following this tutorial: https://www.kite.com/python/answers/how-to-generate-random-colors-in-matplotlib-in-python
I tried to do:
colors = np.random.rand(1,3)
trace_1 = go.Scatter(x = date,
y = value1,
mode = 'markers+lines',
marker_color = colors,
name = '1')
trace_2 = go.Scatter(x = date,
y = value2,
mode = 'markers+lines',
marker_color = colors,
name = '2')
data_total = [trace_1, trace_2]
fig = go.Figure(data=data_total, layout=layout)
py.iplot(fig)
But this code doesn't work.
You should only need to comment out marker_color. Many plotting libraries (plotly included) tend to automatically assign colors.
It seems that the example code on the plotly website for choropleth maps is out of date and no longer works.
The error I'm getting is:
PlotlyError: Invalid 'figure_or_data' argument. Plotly will not be able to properly parse the resulting JSON. If you want to send this 'figure_or_data' to Plotly anyway (not recommended), you can set 'validate=False' as a plot option.
Here's why you're seeing this error:
The entry at index, '0', is invalid because it does not contain a valid 'type' key-value. This is required for valid 'Data' lists.
Path To Error:
['data'][0]
The code that I'm trying to run is shown below. It is copied as-is from the plotly website. Anyone have any ideas as to how I can fix it?
import plotly.plotly as py
import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_us_ag_exports.csv')
for col in df.columns:
df[col] = df[col].astype(str)
scl = [[0.0, 'rgb(242,240,247)'],[0.2, 'rgb(218,218,235)'],[0.4, 'rgb(188,189,220)'],\
[0.6, 'rgb(158,154,200)'],[0.8, 'rgb(117,107,177)'],[1.0, 'rgb(84,39,143)']]
df['text'] = df['state'] + '<br>' +\
'Beef '+df['beef']+' Dairy '+df['dairy']+'<br>'+\
'Fruits '+df['total fruits']+' Veggies ' + df['total veggies']+'<br>'+\
'Wheat '+df['wheat']+' Corn '+df['corn']
data = [ dict(
type='choropleth',
colorscale = scl,
autocolorscale = False,
locations = df['code'],
z = df['total exports'].astype(float),
locationmode = 'USA-states',
text = df['text'],
marker = dict(
line = dict (
color = 'rgb(255,255,255)',
width = 2
)
),
colorbar = dict(
title = "Millions USD"
)
) ]
layout = dict(
title = '2011 US Agriculture Exports by State<br>(Hover for breakdown)',
geo = dict(
scope='usa',
projection=dict( type='albers usa' ),
showlakes = True,
lakecolor = 'rgb(255, 255, 255)',
),
)
fig = dict(data=data, layout=layout)
url = py.plot(fig, filename='d3-cloropleth-map')
fig should be of the Figure type. Use the Choropleth graph object:
import plotly.graph_objs as go
...
data = [go.Choropleth(
colorscale = scl,
autocolorscale = False,
locations = df['code'],
z = df['total exports'].astype(float),
locationmode = 'USA-states',
text = df['text'],
marker = dict(
line = dict(
color = 'rgb(255,255,255)',
width = 2)),
colorbar = dict(
title = "Millions USD")
)]
...
fig = go.Figure(data=data, layout=layout)
...
I wanted to make a choropleth world map, which shows the hits(number of searches) of a word, on a World map.
Following is the code:
import plotly
import plotly.offline
import pandas as pd
df = pd.read_excel('F:\\Intern\\csir\\1yr\\news\\region_2016_2017.xlsx')
df = df.query('keyword==["addiction"]')
scl = [[0.0, 'rgb(242,240,247)'],[0.2, 'rgb(218,218,235)'],[0.4, 'rgb(188,189,220)'],\
[0.6, 'rgb(158,154,200)'],[0.8, 'rgb(117,107,177)'],[1.0, 'rgb(84,39,143)']]
data = [dict(
type='choropleth',
colorscale=scl,
locations = df['location'],
z = df['hits'].astype(int),
locationmode = "country names",
autocolorscale = False,
reversescale = False,
marker = dict(
line = dict (
color = 'rgb(180,180,180)',
width = 0.5)),
colorbar = dict(
autotick = False,
title = 'Hits'),)]
layout = dict(
title = 'Addiction keyword 1yr analysis',
geo = dict(
showframe = False,
showcoastlines = False,
projection = dict(
type = 'Mercator'
)
)
)
fig = dict(data = data,layout = layout)
plotly.offline.plot(fig,validate=False,filename = 'd3-world-map.html')
And the plotted map is:
As one can see clearly, many countries are missing. This may be due to the fact that many countries didn't have entries which explicitly stated that they have zero hits.
I don't want to explicitly do that with my data. Is there any other way out of this? So that we can see all of the countries.
Data set can be found here.
Note that the dataset that I've linked is an .csv file whereas the file used in the program is an .xlsx version of the file.
You need to turn on country outlines under layout...
"geo":{
"countriescolor": "#444444",
"showcountries": true
},
As far as I'm aware, I've copied the documentation exactly. I basically used the documentation code and tweaked it for my purposes. But when I run this bit of code, no hover feature with text appears on my plot.
#Initialize df
aviation_data = pd.DataFrame(columns=["Latitude","Longitude","Fatalities"])
aviation_data["Latitude"] = [40.53666,60.94444]
aviation_data["Longitude"] = [-81.955833,-159.620834]
aviation_data["Fatalities"] = [True,False]
#Initialize colorscale
scl = [[0,"rgb(216,15,15)"],[1,"rgb(5,10,172)"]]
#Initialize text data
text_df = "Fatal: " + aviation_data["Fatalities"].apply(lambda x: str(np.bool(x))) + '<br>' + \
"Latitude: " + aviation_data["Latitude"].apply(lambda x: str(x)) + '<br>' + \
"Longitude" + aviation_data["Longitude"].apply(lambda x: str(x))
#Initialize data
data = [ dict(
type = 'scattergeo',
locationmode = 'USA-states',
lon = aviation_data["Longitude"],
lat = aviation_data["Latitude"],
text = text_df,
mode = 'markers',
marker = dict(
size = 5,
opacity = 0.5,
reversescale=True,
autocolorscale=False,
symbol = 'circle',
line = dict(
width=1,
color='rgba(102, 102, 102)'
),
colorscale = scl,
cmin = 0,
color = aviation_data["Fatalities"].astype(int),
cmax = 1
))]
#Initialize layout
layout = dict(
title ='Aviation Incidents for the Years 2014-2016<br>\
(red indicates fatal incident, blue indicates non-fatal)',
geo = dict(
scope='usa',
projection=dict(type='albers usa'),
showland = True,
landcolor = "rgb(206, 206, 206)",
countrywidth = 0.5,
subunitwidth = 0.5
),
)
#Plot
fig = dict(data=data,layout=layout)
iplot(fig,validate=False)
Anyone know why my hover text isn't showing up?
In the last line of code you need to call this:
plotly.offline.plot(fig, validate=False)
Instead of:
iplot(fig, validate=False)
Also do not forget import plotly:
import plotly
Hope this will help