Reputation: 129
python plotly: unfixed number of traces
My code reads data from .xlsx file and it plots the Bubble diagram by using plotly. Bubble Diagram The task is easy when I do know how many traces need to be plot. However, I was thrown into bewilderment when the number of traces is unfixed since the number of rows is variable.
1991 1992 1993 1994 1995 1996 1997
US 10 14 16 18 20 42 64
JAPAN 100 30 70 85 30 42 64
CN 50 22 30 65 70 66 60
Here is my uncompleted code：
# Version 2 could read data from .xlsx file.
import plotly as py
import plotly.graph_objs as go
import openpyxl
wb = openpyxl.load_workbook(('grape output.xlsx'))
sheet = wb['Sheet1']
row_max = sheet.max_row
col_max = sheet.max_column
l=[]
for row_n in range(row_max-1):
l.append([])
for col_n in range(col_max-1):
l[row_n].append(sheet.cell(row=row_n+2, column=col_n+2).value)
trace0 = go.Scatter(
x=[1991, 1992, 1993, 1994, 1995, 1996, 1997],
y=['US', 'US', 'US', 'US', 'US', 'US', 'US'],
mode='markers+text',
marker=dict(
color='rgb(150,204,90)',
size= l[0],
showscale = False,
),
text=list(map(str, l[0])),
textposition='middle center',
)
trace1 = go.Scatter(
x=[1991, 1992, 1993, 1994, 1995, 1996, 1997],
y=['JAPAN', 'JAPAN', 'JAPAN', 'JAPAN', 'JAPAN', 'JAPAN', 'JAPAN'],
mode='markers+text',
marker=dict(
color='rgb(255, 130, 71)',
size=l[1],
showscale=False,
),
text=list(map(str,l[1])),
textposition='middle center',
)
trace2 = go.Scatter(
x=[1991, 1992, 1993, 1994, 1995, 1996, 1997],
y=['CN', 'CN', 'CN', 'CN', 'CN', 'CN', 'CN'],
mode='markers+text',
marker=dict(
color='rgb(255, 193, 37)',
size=l[2],
showscale=False,
),
text=list(map(str,l[2])),
textposition='middle center',
)
layout = go.Layout(plot_bgcolor='rgb(10, 10, 10)',
paper_bgcolor='rgb(20, 55, 100)',
font={
'size': 15,
'family': 'sans-serif',
'color': 'rgb(255, 255, 255)'
},
width=1000,
height=500,
xaxis=dict(title='Output of grapes per year in US, JAPAN and CN', ),
showlegend=False,
margin=dict(l=100, r=100, t=100, b=100),
hovermode = False,
)
data = [trace0, trace1, trace2]
fig = go.Figure(data=data, layout=layout)
py.offline.init_notebook_mode()
py.offline.plot(fig, filename='basic-scatter.html')
Could you please teach me how to draw them? Thx
Upvotes: 1
Views: 398
Answers (3)
Reputation: 129
Code has been updated to Version 2 which could read data from .xlsx file and plot Bubble Diagram. The raw data named 'grape output.xlsx' has been added with new items in comparison with the previous one:
1991 1992 1993 1994 1995 1996 1997 1998 1999
US 10 14 16 18 20 42 64 100 50
JAPAN 100 30 70 85 30 42 64 98 24
CN 50 22 30 65 70 66 60 45 45
INDIA 90 88 35 50 90 60 40 66 76
UK 40 50 70 50 25 30 22 40 60
Here is the code:
# Version 2
import plotly as py
import plotly.graph_objs as go
import openpyxl
import pandas as pd
wb = openpyxl.load_workbook('grape output.xlsx')
sheet = wb['Sheet1']
row_max = sheet.max_row
col_max = sheet.max_column
first_row_list = []
first_col_list = []
for col_n in range(2, col_max+1):
first_row_list.append(sheet.cell(row=1, column=col_n).value)
for row_n in range(2,row_max+1):
first_col_list.append(sheet.cell(row=row_n, column=1).value)
data_all = pd.read_excel('grape output.xlsx')
data = data_all.loc[:,first_row_list]
df = pd.DataFrame(data)
df.index = first_col_list
colors = ['rgb(150,204,90)','rgb(255, 130, 71)','rgb(255, 193, 37)','rgb(180,240,190)','rgb(255, 10, 1)',
'rgb(25, 19, 3)','rgb(100, 100, 100)','rgb(45,24,200)','rgb(33, 58, 108)','rgb(35, 208, 232)']
data = [go.Scatter(
x=df.columns,
y=[country]*len(df.columns),
mode='markers+text',
marker=dict(
color=colors[num],
size= df.loc[country],
showscale = False,
),
text=list(map(str, df.loc[country])),
textposition='middle center',
)
for num, country in enumerate(reversed(df.index))
]
layout = go.Layout(plot_bgcolor='rgb(10, 10, 10)',
paper_bgcolor='rgb(20, 55, 100)',
font={
'size': 15,
'family': 'sans-serif',
'color': 'rgb(255, 255, 255)'
},
width=1000,
height=800,
xaxis=dict(title='Output of grapes per year in US, JAPAN and CN'),
showlegend=False,
margin=dict(l=100, r=100, t=100, b=100),
hovermode = False,
)
fig = go.Figure(data=data, layout=layout)
py.offline.plot(fig, filename='basic-scatter.html')
Now the result is like this:
There remains some little problems:
- How to get rid of the two numbers 1990 and 2000 as well as white vertical lines for 1990 and 2000?
- How to draw white lines for 1991, 1993, 1995, 1997，1999 and display all these years as abscissa axis?
Please make corrections for code Versinon 2 to improve it. Thank you！
Upvotes: 0
Reputation: 13437
Derek O.'s answer is perfect but i think there is a more flexible way to do it using plotly.express this in particular if you don't want to define the colors.
The idea is to properly transform the data.
Data
import pandas as pd
df = pd.DataFrame({1991:[10,100,50], 1992:[14,30,22], 1993:[16,70,30], 1994:[18,85,65], 1995:[20,30,70], 1996:[42,42,66], 1997:[64,64,60]})
df.index = ['US','JAPAN','CN']
df = df.T.unstack()\
.reset_index()\
.rename(columns={"level_0": "country",
"level_1": "year",
0: "n"})
print(df)
country year n
0 US 1991 10
1 US 1992 14
2 US 1993 16
3 US 1994 18
4 US 1995 20
5 US 1996 42
6 US 1997 64
7 JAPAN 1991 100
8 JAPAN 1992 30
9 JAPAN 1993 70
10 JAPAN 1994 85
11 JAPAN 1995 30
12 JAPAN 1996 42
13 JAPAN 1997 64
14 CN 1991 50
15 CN 1992 22
16 CN 1993 30
17 CN 1994 65
18 CN 1995 70
19 CN 1996 66
20 CN 1997 60
Using plotly.express
Now that your data is in a long format you can use plotly.express as following
import plotly.express as px
fig = px.scatter(df,
x="year",
y="country",
size="n",
color="country",
text="n",
size_max=50 # you need this otherwise the bubble are too small
)
fig.update_layout(plot_bgcolor='rgb(10, 10, 10)',
paper_bgcolor='rgb(20, 55, 100)',
font={'size': 15,
'family': 'sans-serif',
'color': 'rgb(255, 255, 255)'
},
width=1000,
height=500,
xaxis=dict(title='Output of grapes per year in selected countries', ),
showlegend=False,
margin=dict(l=100, r=100, t=100, b=100),
hovermode = False,)
# Uncomment this if you don't wont country as yaxis title
# fig.layout.yaxis.title.text = None
fig.show()
Upvotes: 3
Reputation: 19545
I should point out that your code would be more reproducible if you attached your raw data as text or something that can be more easily copy and pasted. However, I can still answer your question and point you in the right direction regardless.
What you should do is use a loop, and start by looking at the line data = [trace0, trace1, trace2]. As you noticed, this method won't scale up if you have 100 countries instead of 3.
Instead, you can create the data as a list using a list comprehension, and updating the part of each trace that changes. trace0, trace1, trace2 aren't much different except for the country, values, and colors. To show you what I mean, I recreated your data using a DataFrame, then created individual lists containing your countries and colors.
# Version 2 could read data from .xlsx file.
import plotly as py
import plotly.graph_objs as go
import openpyxl
# wb = openpyxl.load_workbook(('grape output.xlsx'))
# sheet = wb['Sheet1']
# row_max = sheet.max_row
# col_max = sheet.max_column
# l=[]
# for row_n in range(row_max-1):
# l.append([])
# for col_n in range(col_max-1):
# l[row_n].append(sheet.cell(row=row_n+2, column=col_n+2).value)
import pandas as pd
df = pd.DataFrame({1991:[10,100,50], 1992:[14,30,22], 1993:[16,70,30], 1994:[18,85,65], 1995:[20,30,70], 1996:[42,42,66], 1997:[64,64,60]})
df.index = ['US','JAPAN','CN']
colors = ['rgb(150,204,90)','rgb(255, 130, 71)','rgb(255, 193, 37)']
data = [go.Scatter(
x=df.columns,
y=[country]*len(df.columns),
mode='markers+text',
marker=dict(
color=colors[num],
size= df.loc[country],
showscale = False,
),
text=list(map(str, df.loc[country])),
textposition='middle center',
)
for num, country in enumerate(df.index)
]
layout = go.Layout(plot_bgcolor='rgb(10, 10, 10)',
paper_bgcolor='rgb(20, 55, 100)',
font={
'size': 15,
'family': 'sans-serif',
'color': 'rgb(255, 255, 255)'
},
width=1000,
height=500,
xaxis=dict(title='Output of grapes per year in US, JAPAN and CN', ),
showlegend=False,
margin=dict(l=100, r=100, t=100, b=100),
hovermode = False,
)
# data = [trace0, trace1, trace2]
fig = go.Figure(data=data, layout=layout)
fig.show()
# py.offline.init_notebook_mode()
# py.offline.plot(fig, filename='basic-scatter.html')
If I then add a test country to the DataFrame with values for 1991-1997, I don't need to change the rest of the code and the bubble plot will update accordingly.
# I added a test country with data
df = pd.DataFrame({1991:[10,100,50,10], 1992:[14,30,22,20], 1993:[16,70,30,30], 1994:[18,85,65,40], 1995:[20,30,70,50], 1996:[42,42,66,60], 1997:[64,64,60,70]})
df.index = ['US','JAPAN','CN','TEST']
colors = ['rgb(150,204,90)','rgb(255, 130, 71)','rgb(255, 193, 37)','rgb(100, 100, 100)']
Upvotes: 2
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