Plot Multiple Boxplot in One Graph

Plot multiple boxplot in one graph

You should get your data in a specific format by melting your data (see below for how melted data looks like) before you plot. Otherwise, what you have done seems to be okay.

require(reshape2)
df <- read.csv("TestData.csv", header=T)
# melting by "Label". `melt is from the reshape2 package. 
# do ?melt to see what other things it can do (you will surely need it)
df.m <- melt(df, id.var = "Label")
> df.m # pasting some rows of the melted data.frame

#     Label variable      value
# 1    Good       F1 0.64778924
# 2    Good       F1 0.54608791
# 3    Good       F1 0.46134200
# 4    Good       F1 0.79421221
# 5    Good       F1 0.56919951
# 6    Good       F1 0.73568570
# 7    Good       F1 0.65094207
# 8    Good       F1 0.45749702
# 9    Good       F1 0.80861929
# 10   Good       F1 0.67310067
# 11   Good       F1 0.68781739
# 12   Good       F1 0.47009455
# 13   Good       F1 0.95859182
# 14   Good       F1 1.00000000
# 15   Good       F1 0.46908343
# 16    Bad       F1 0.57875528
# 17    Bad       F1 0.28938046
# 18    Bad       F1 0.68511766

require(ggplot2)
ggplot(data = df.m, aes(x=variable, y=value)) + geom_boxplot(aes(fill=Label))

Edit: I realise that you might need to facet. Here's an implementation of that as well:

p <- ggplot(data = df.m, aes(x=variable, y=value)) + 
             geom_boxplot(aes(fill=Label))
p + facet_wrap( ~ variable, scales="free")

Edit 2: How to add x-labels, y-labels, title, change legend heading, add a jitter?

p <- ggplot(data = df.m, aes(x=variable, y=value)) 
p <- p + geom_boxplot(aes(fill=Label))
p <- p + geom_jitter()
p <- p + facet_wrap( ~ variable, scales="free")
p <- p + xlab("x-axis") + ylab("y-axis") + ggtitle("Title")
p <- p + guides(fill=guide_legend(title="Legend_Title"))
p 

Edit 3: How to align geom_point() points to the center of box-plot? It could be done using position_dodge. This should work.

require(ggplot2)
p <- ggplot(data = df.m, aes(x=variable, y=value)) 
p <- p + geom_boxplot(aes(fill = Label))
# if you want color for points replace group with colour=Label
p <- p + geom_point(aes(y=value, group=Label), position = position_dodge(width=0.75))
p <- p + facet_wrap( ~ variable, scales="free")
p <- p + xlab("x-axis") + ylab("y-axis") + ggtitle("Title")
p <- p + guides(fill=guide_legend(title="Legend_Title"))
p 

Plot multiple boxplot in one graph in pandas or matplotlib?

Use return_type='axes' to get a1.boxplot to return a matplotlib Axes object.
Then pass that axes to the second call to boxplot using ax=ax. This will cause both boxplots to be drawn on the same axes.

a1=a[['kCH4_sync','week_days']]
ax = a1.boxplot(by='week_days', meanline=True, showmeans=True, showcaps=True, 
                showbox=True, showfliers=False, return_type='axes')
a2 = a[['CH4_sync','week_days']]
a2.boxplot(by='week_days', meanline=True, showmeans=True, showcaps=True, 
           showbox=True, showfliers=False, ax=ax)

Plotting several boxplots from different dataframes in one graph

You could create a new dataframe, with a column for each of the given dataframes. Pandas will pad the columns with NaNs to compensate for the different lengths.

import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np

df1 = pd.DataFrame({'Numbers': np.random.normal(.1, 1, np.random.randint(30, 100)).cumsum()})
df2 = pd.DataFrame({'Numbers': np.random.normal(.2, 1, np.random.randint(30, 100)).cumsum()})
df3 = pd.DataFrame({'Numbers': np.random.normal(.3, 1, np.random.randint(30, 100)).cumsum()})
df4 = pd.DataFrame({'Numbers': np.random.normal(.4, 1, np.random.randint(30, 100)).cumsum()})

combined_dfs = pd.DataFrame({'df1': df1['Numbers'],
                             'df2': df2['Numbers'],
                             'df3': df3['Numbers'],
                             'df4': df4['Numbers']})
sns.set_style('white')
sns.boxplot(data=combined_dfs, palette='flare')
sns.despine()
plt.show()

How to plot multiple boxplot in one graph for R 2020

What's wrong with just using boxplot? No ggplot2, and that should work in your version, too.

However, it's not unambiguous what you mean by "multiple box plots in one graph". Here three versions:

## by social group
op <- par(mfrow=c(1, 2))  ## set par
boxplot(Absenteeism.time.in.hours ~ Social.smoker, dat)
boxplot(Absenteeism.time.in.hours ~ Social.drinker, dat)
par(op)  ## reset par

## by social group in one panel 
datl <- reshape(dat, varying=2:3, direction="long")
boxplot(Absenteeism.time.in.hours ~ time + Social, datl)

## social group interaction
boxplot(Absenteeism.time.in.hours ~ ., dat)

---

Data:

dat <- read.table(header=T, text="   Absenteeism.time.in.hours Social.smoker Social.drinker
1                          4             0              1
2                          0             0              1
3                          2             0              1
4                          4             1              1
5                          2             0              1
6                          2             0              1
7                          8             0              1
8                          4             0              1
9                         40             0              1
10                         8             0              0
11                         8             0              1
12                         8             0              1
13                         8             0              1
14                         1             0              1
15                         4             0              1
16                         8             0              1
17                         2             0              1
18                         8             1              1
19                         8             0              0
20                         2             1              0")

Creating multiple boxplots on the same graph from a dictionary

my_dict = {'ABC': [34.54, 34.345, 34.761], 'DEF': [34.541, 34.748, 34.482]}

fig, ax = plt.subplots()
ax.boxplot(my_dict.values())
ax.set_xticklabels(my_dict.keys())

Create multiple boxplots from statistics in one graph

You can pass a list of dictionaries to the bxp method. The easiest way to get such a list from your existing code is to put the dictionary construction inside a function and call it for each row of the dataframe.

Note that data.iloc[:, 0] would be the first column, not the first row.

import matplotlib.pyplot as plt
import pandas as pd


def stats(row):
    return {"med": row["sharpeRatio_med"],
            "q1": row["sharpeRatio_q1"],
            "q3": row["sharpeRatio_q3"],
            "whislo": row["sharpeRatio_min"],  
            "whishi": row["sharpeRatio_max"]}


data = pd.DataFrame({"sharpeRatio_med": [3, 4, 2],
                     "sharpeRatio_q1": [2, 3, 1],
                     "sharpeRatio_q3": [4, 5, 3],
                     "sharpeRatio_min": [1, 1, 0],  
                     "sharpeRatio_max": [5, 6, 4]})

fig, axes = plt.subplots()
axes.bxp([stats(data.iloc[i, :]) for i in range(len(data))],
         showfliers=False)
plt.show()

plot multiple boxplot in one graph ( one column is list of data) by Plotly or other way

Here is the way I solve this problem.

nn = list_hour_df.explode('list_hour').reset_index(drop=True)

nn['list_hour'] = nn['list_hour'].astype(int)

nn

0   Active Life     22
1   Active Life     21
2   Active Life     18
3   Active Life     23
4   Active Life     20
... ... ...
396416  Shopping    8
396417  Shopping    13
396418  Shopping    21
396419  Shopping    19
396420  Shopping    4

fig = px.box(nn, x="list_hour", y="Main_Category")

fig.show()
enter image description here

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