I want to plot boxplot of multiple columns of a dataframe. With R, I'm able to play with the axis and set different ranges to show the plots the way I want. In python though, I can have only one range and cannot set different range for different columns. How I can plot boxplot in python similar to ggplot2?
The snip of my code is as follow. I also put the results of ggplot, seaborn and plotly.
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = pd.read_excel('data-rta-3phase-boxplot.xlsx', header=0)
sns.boxplot(x="variable", y="value", data=pd.melt(df))
plt.show()
import plotly.graph_objects as go
fig = go.Figure()
for col in df:
fig.add_trace(go.Box(y=df[col].values, name=df[col].name))
fig.show()
What I want looks like this (created with ggplot2 in R)
and these are what I get in plotly and seaborn
UPDATE!!!!!
With the guidance from the community, I managed to create a fully controllable code to draw boxplots.
import pandas as pd
import plotly.express as px
df = pd.read_excel('data-rta-3phase-boxplot.xlsx', header=0)
fig = px.box(df.melt(), y="value", facet_col="variable", boxmode="overlay", color="variable")
fig.update_yaxes(matches=None)
for i in range(len(fig["data"])):
yaxis_name = 'yaxis' if i == 0 else f'yaxis{i + 1}'
fig.layout[yaxis_name].showticklabels = True
fig.update_layout(legend = dict(bgcolor = 'white'))
fig.update_layout(plot_bgcolor='white')
fig.update_xaxes(showline=True, linewidth=2, linecolor='black')#, mirror=True)
fig.update_yaxes(showline=True, linewidth=2, linecolor='black')#, mirror=True)
fig.update_xaxes(showgrid=True, gridwidth=1, gridcolor='gray')
fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='gray')
fig.show()
