Plotting a Stacked Bar Plot

Single Stacked Bar Chart Matplotlib

First transpose one column DataFrame:

df.T.plot.barh(stacked=True, legend=False)

If 2 or more columns:

df[['Percentage']].T.plot.barh(stacked=True, legend=False)

plotting stacked bar graph

With Python 3.9.7, your graphs look like the same:

>>> df_alpha
       a   b   c   d   e   f   g   h   i   j   k   l
2016  20  20  20  20  20  20  20  20  20  20  20  20
2017   0  13  20  20  20  20  20  20  20  20  20  20
2018   0  10  10  10  10  10  10  10  10  10  10   0
2019   0  18  15  15  15  15  15  15  15  15  15   0
2020  10  15  18  18  18  18  18  18  18  18  18   0
2021  21  45  78  75  78  78  78  78  78  78  78  20

>>> df_month
      January  February  March  April  may  June  July  August  September  October  November  December
2016       20        20     20     20   20    20    20      20         20       20        20        20
2017        0        13     20     20   20    20    20      20         20       20        20        20
2018        0        10     10     10   10    10    10      10         10       10        10         0
2019        0        18     15     15   15    15    15      15         15       15        15         0
2020       10        15     18     18   18    18    18      18         18       18        18         0
2021       21        45     78     75   78    78    78      78         78       78        78        20

Full-code:

import pandas as pd
import matplotlib.pyplot as plt

years = ['2016', '2017', '2018', '2019', '2020', '2021']

dataavail1 = {'a': [20, 0, 0, 0, 10, 21], 'b': [20, 13, 10, 18, 15, 45], 'c': [20, 20, 10, 15, 18, 78], 'd': [20, 20, 10, 15, 18, 75], 'e': [20, 20, 10, 15, 18, 78], 'f': [20, 20, 10, 15, 18, 78], 'g': [20, 20, 10, 15, 18, 78], 'h': [20, 20, 10, 15, 18, 78], 'i': [20, 20, 10, 15, 18, 78], 'j': [20, 20, 10, 15, 18, 78], 'k': [20, 20, 10, 15, 18, 78], 'l': [20, 20, 0, 0, 0, 20]}

dataavail2 = {'January': [20, 0, 0, 0, 10, 21], 'February': [20, 13, 10, 18, 15, 45], 'March': [20, 20, 10, 15, 18, 78], 'April': [20, 20, 10, 15, 18, 75], 'may': [20, 20, 10, 15, 18, 78], 'June': [20, 20, 10, 15, 18, 78], 'July': [20, 20, 10, 15, 18, 78], 'August': [20, 20, 10, 15, 18, 78], 'September': [20, 20, 10, 15, 18, 78], 'October': [20, 20, 10, 15, 18, 78], 'November': [20, 20, 10, 15, 18, 78], 'December': [20, 20, 0, 0, 0, 20]}

df_alpha = pd.DataFrame(dataavail1, index=years)
df_month = pd.DataFrame(dataavail2, index=years)

fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 8))
df_alpha.plot(kind='bar', stacked=True, colormap=plt.cm.tab20, ax=ax1, rot=0)
df_month.plot(kind='bar', stacked=True, colormap=plt.cm.tab20, ax=ax2, rot=0)
plt.show()

Update: the code also works with Python 3.7.12

plotting multiple stacked bar chart

IIUC, try:

import matplotlib.pyplot as plt

fig, ax = plt.subplots(1, 5, figsize=(20, 8))
iax = iter(ax.flatten())
for n, g in df.groupby('Business Unit'):
    g.loc[n, :].plot.bar(ax=next(iax), title=f'{n}', stacked=True)

Draw a stacked bar chart from multiple columns instead of drawing a graph for each column?

It can be achieved by rearranging the dataframe using groupby. Consider the code:

df_responses= pd.read_csv('https://raw.githubusercontent.com/eng-aomar/Security_in_practice/main/secuirtyInPractice.csv')

df_new =df_responses.iloc[:,9:21]
image_format = 'svg' # e.g .png, .svg, etc.

# initialize empty dataframe
df2 = pd.DataFrame()

# group by each column counting the size of each category values
for col in df_new:
    grped = df_new.groupby(col).size()
    grped = grped.rename(grped.index.name)
    df2 = df2.merge(grped.to_frame(), how='outer', left_index=True, right_index=True)

# plot the merged dataframe
df2.plot.bar(stacked=True)
plt.show()

Using your data and notebook. This is what I get:

Stacked Bar Graphs with only Plotly Express

You can create a dataframe and structure it from your lists. Then it's simple to use Plotly Express

import plotly.express as px
import pandas as pd

labels = ["label1", "label2", "label3"]
types = ["type1", "type2", "type3", "type4", "type5", "type6"]
counts = [[3, 5, 2, 1, 7, 10], [2, 2, 4, 1, 7, 2], [1, 6, 8, 11, 2, 3]]

px.bar(
    pd.DataFrame(counts, columns=types, index=labels).reset_index().melt(id_vars="index"),
    x="index",
    y="value",
    color="variable",
)

numpy

import numpy as np

c = np.array(counts)
px.bar(x=np.tile(labels, c.shape[1]), color=np.repeat(types, c.shape[0]), y=c.T.flatten())

Matplotlib stacked bar chart set column order

to set a custom order for the stacked bars, you will need to order it by setting the CategoricalIndex and sorting the data by these categories. This will sort the three categories in the way you need. A small example to show the same is below...

Data 'df'

Intervention    Remuneration    Training    Supervision
A   21  4   12
B   41  5   21
C   33  6   7

Code

#Convert Intervention as index, so columns are the categories
df = df.set_index('Intervention') 

#Set categories... Order will Remuneration-Training-Supervision
df.columns=pd.CategoricalIndex(df.columns.values, ordered=True, categories=['Remuneration','Training','Supervision'])

#Sort the data
df = df.sort_index(axis=1)

#...and plot
bar = df.plot.barh(stacked=True)

Output

How to implement stacked bar graph with a line chart in R

You first need to reshape longer, for example with pivot_longer() from tidyr, and then you can use ggplot2 to plot the bars and the line in two separate layers. The fill = argument in the geom_bar(aes()) lets you stratify each bar according to a categorical variable - name is created automatically by pivot_longer().

library(ggplot2)
library(tidyr)

dat |> 
  pivot_longer(A:B) |> 
  ggplot(aes(x = Year)) +
  geom_bar(stat = "identity", aes(y = value, fill = name)) +
  geom_line(aes(y = `C(%)`), size = 2)

^{Created on 2022-06-09 by the reprex package (v2.0.1)}

You're asking for overlaid bars, in which case there's no need to pivot, and you can add separate layers. However I would argue that this could confuse or mislead many people - usually in stacked plots bars are stacked, not overlaid, so thread with caution!

library(ggplot2)
library(tidyr)

dat |> 
  ggplot(aes(x = Year)) +
  geom_bar(stat = "identity", aes(y = A), fill = "lightgreen") +
  geom_bar(stat = "identity", aes(y = B), fill = "red", alpha = 0.5) +
  geom_line(aes(y = `C(%)`), size = 2) +
  labs(y = "", caption = "NB: bars are overlaid, not stacked!")

^{Created on 2022-06-09 by the reprex package (v2.0.1)}

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