How can I use Plotly to produce a line plot with a shaded standard deviation? I am trying to achieve something similar to seaborn.tsplot. Any help is appreciated.
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Answer
The following approach is fully flexible with regards to the number of columns in a pandas dataframe and uses the default color cycle of plotly. If the number of lines exceed the number of colors, the colors will be re-used from the start. As of now px.colors.qualitative.Plotly
can be replaced with any hex color sequence that you can find using px.colors.qualitative
:
Alphabet = ['#AA0DFE', '#3283FE', '#85660D', '#782AB6', '#565656', '#1... Alphabet_r = ['#FA0087', '#FBE426', '#B00068', '#FC1CBF', '#C075A6', '... [...]
Complete code:
# imports import plotly.graph_objs as go import plotly.express as px import pandas as pd import numpy as np # sample data in a pandas dataframe np.random.seed(1) df=pd.DataFrame(dict(A=np.random.uniform(low=-1, high=2, size=25).tolist(), B=np.random.uniform(low=-4, high=3, size=25).tolist(), C=np.random.uniform(low=-1, high=3, size=25).tolist(), )) df = df.cumsum() # define colors as a list colors = px.colors.qualitative.Plotly # convert plotly hex colors to rgba to enable transparency adjustments def hex_rgba(hex, transparency): col_hex = hex.lstrip('#') col_rgb = list(int(col_hex[i:i+2], 16) for i in (0, 2, 4)) col_rgb.extend([transparency]) areacol = tuple(col_rgb) return areacol rgba = [hex_rgba(c, transparency=0.2) for c in colors] colCycle = ['rgba'+str(elem) for elem in rgba] # Make sure the colors run in cycles if there are more lines than colors def next_col(cols): while True: for col in cols: yield col line_color=next_col(cols=colCycle) # plotly figure fig = go.Figure() # add line and shaded area for each series and standards deviation for i, col in enumerate(df): new_col = next(line_color) x = list(df.index.values+1) y1 = df[col] y1_upper = [(y + np.std(df[col])) for y in df[col]] y1_lower = [(y - np.std(df[col])) for y in df[col]] y1_lower = y1_lower[::-1] # standard deviation area fig.add_traces(go.Scatter(x=x+x[::-1], y=y1_upper+y1_lower, fill='tozerox', fillcolor=new_col, line=dict(color='rgba(255,255,255,0)'), showlegend=False, name=col)) # line trace fig.add_traces(go.Scatter(x=x, y=y1, line=dict(color=new_col, width=2.5), mode='lines', name=col) ) # set x-axis fig.update_layout(xaxis=dict(range=[1,len(df)])) fig.show()