[英]Seaborn/Plotly multiple y-axes
I would like to get a plot with more than two different y-axes in seaborn using a pandas dataframe similar to this example for matlotlib: https://matplotlib.org/examples/axes_grid/demo_parasite_axes2.html
因为它将在 function 中使用,所以我想灵活地选择 Pandas dataframe 的列数和列。
不幸的是 Seaborn 似乎只移动了最后添加的比例。 这是我想要对 Seaborn 示例数据集执行的操作:
import matplotlib.colors as mcolors
import matplotlib.pyplot as plt
import seaborn as sns
df=sns.load_dataset("mpg")
df=df.loc[df['model_year']<78]
show=['mpg','displacement','acceleration']
sns.set(rc={'figure.figsize':(11.7,8.27)})
sns.scatterplot('weight',show[0],data=df.reset_index(),style='model_year')
del show[0]
k=1
off=0
for i in show:
a = plt.twinx()
a=sns.scatterplot('weight',i,data=df.reset_index(),ax=a, color=list(mcolors.TABLEAU_COLORS)[k],legend=False,style='model_year')
a.spines['right'].set_position(('outward', off))
a.yaxis.label.set_color(list(mcolors.TABLEAU_COLORS)[k])
k+=1
off+=60
我想创建一个 function 可以灵活地 plot 不同的列。 到目前为止,这在 plotly 对我来说似乎相当复杂(没办法只做一个循环)。 如果有好的方法,我也会用 go 和 plotly。
Plotly 实际上有一个好方法,您可以查看下图的代码示例,类似于文档本节中的matplotlib 示例。
我现在使用 plotly 实现了这个。
import seaborn as sns
import plotly.graph_objects as go
df=sns.load_dataset("mpg")
show=['mpg','displacement','acceleration']
mcolors=[
'#1f77b4', # muted blue
'#ff7f0e', # safety orange
'#2ca02c', # cooked asparagus green
'#d62728', # brick red
'#9467bd', # muted purple
'#8c564b', # chestnut brown
'#e377c2', # raspberry yogurt pink
'#7f7f7f', # middle gray
'#bcbd22', # curry yellow-green
'#17becf' # blue-teal
];
fig = go.Figure()
m=0
for k in df.model_year.unique():
fig.add_trace(go.Scatter(
x = df.loc[df.model_year == k]['weight'],
y = df.loc[df.model_year == k][show[0]],
name = str(k),
mode = 'markers',
marker_symbol=m,
marker_line_width=0,
marker_size=6,
marker_color=mcolors[0],
))
m+=1
layout = {'xaxis':dict(
domain=[0,0.7]
),
'yaxis':dict(
title=show[0],
titlefont=dict(
color=mcolors[0]
),
tickfont=dict(
color=mcolors[0]
),
showgrid=False
)}
n=2
for i in show[1::]:
m=0
for k in df.model_year.unique():
fig.add_trace(go.Scatter(
x = df.loc[df.model_year == k]['weight'],
y = df.loc[df.model_year == k][i],
name = str(k),
yaxis ='y'+str(n),
mode = 'markers',
marker_symbol=m,
marker_line_width=0,
marker_size=6,
marker_color=mcolors[n],
showlegend = False
))
m+=1
layout['yaxis'+str(n)] = dict(
title=i,
titlefont=dict(
color=mcolors[n]
),
tickfont=dict(
color=mcolors[n]
),
anchor="free",
overlaying="y",
side="right",
position=(n)*0.08+0.55,
showgrid=False,
)
n+=1
fig.update_layout(**layout)
fig.show()
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.