[英]python plotly: unfixed number of traces
My code reads data from .xlsx file and it plots the Bubble diagram by using plotly.我的代码从 .xlsx 文件读取数据,并使用 plotly 绘制气泡图。 Bubble Diagram The task is easy when I do know how many traces need to be plot.气泡图当我知道需要绘制多少条轨迹时,任务就很容易了。 However, I was thrown into bewilderment when the number of traces is unfixed since the number of rows is variable.但是,由于行数是可变的,因此当跟踪的数量不固定时,我感到困惑。
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:这是我未完成的代码:
# 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?你能教我怎么画它们吗? Thx谢谢
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. Derek O. 的回答是完美的,但我认为有一种更灵活的方法可以使用plotly.express
这个,特别是如果你不想定义颜色。
The idea is to properly transform the data.这个想法是正确地转换数据。
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
plotly.express
使用plotly.express
Now that your data is in a long format you can use plotly.express
as following现在您的数据是长格式,您可以使用plotly.express
如下
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()
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.我应该指出,如果您将原始数据作为文本或可以更轻松复制和粘贴的内容附加,您的代码将更具可重现性。 However, I can still answer your question and point you in the right direction regardless.但是,无论如何,我仍然可以回答您的问题并为您指明正确的方向。
What you should do is use a loop, and start by looking at the line data = [trace0, trace1, trace2]
.您应该做的是使用循环,并从查看行data = [trace0, trace1, trace2]
。 As you noticed, this method won't scale up if you have 100 countries instead of 3.正如您所注意到的,如果您有 100 个国家而不是 3 个,则此方法不会扩大规模。
Instead, you can create the data
as a list using a list comprehension, and updating the part of each trace that changes.相反,您可以使用列表推导将data
创建为列表,并更新每个跟踪更改的部分。 trace0
, trace1
, trace2
aren't much different except for the country, values, and colors. trace0
、 trace1
、 trace2
除了国家、值和颜色之外没有太大不同。 To show you what I mean, I recreated your data using a DataFrame, then created individual lists containing your countries and colors.为了向您展示我的意思,我使用 DataFrame 重新创建了您的数据,然后创建了包含您的国家/地区和颜色的单独列表。
# 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.如果我随后将一个测试国家/地区添加到 DataFrame 中,其值为 1991-1997,则不需要更改其余代码,气泡图将相应更新。
# 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)']
Code has been updated to Version 2 which could read data from .xlsx file and plot Bubble Diagram.代码已更新到版本 2,它可以从 .xlsx 文件中读取数据并绘制气泡图。 The raw data named 'grape output.xlsx' has been added with new items in comparison with the previous one:与之前的数据相比,名为“grape output.xlsx”的原始数据添加了新项目:
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:这是代码:
# 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:现在的结果是这样的: There remains some little problems:还存在一些小问题:
Please make corrections for code Versinon 2 to improve it.请更正代码 Versinon 2 以改进它。 Thank you!谢谢!
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