Change the stacked bar chart to Stacked Percentage Bar Plot-CodePudding

How can I change this stacked bar into a stacked Percentage Bar Plot with percentage labels:

here is 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()

CodePudding user response：

You can just calculate the percentages yourself e.g. in a new column of your dataframe as you do have the absolute values and plot this column instead. Using sum() and division using dataframes you should get there quickly.

You might wanna have a look at GeeksForGeeks post which shows how this could be done.

EDIT

I have now gone ahead and adjusted your program so it will give the results that you want (at least the result I think you would like). Two key functions that I used and you did not, are df.value_counts() and df.transpose(). You might wanna read on those two as they are quite helpful in many situations.

import pandas as pd
import matplotlib.pyplot as plt
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 providing the columns
df2 = pd.DataFrame(columns=df_new.columns)


# loop over all columns
for col in df_new.columns:
    # counting occurences for each value can be done by value_counts()
    val_counts = df_new[col].value_counts()
    # replace nan values with 0
    val_counts.fillna(0)
    # calculate the sum of all categories
    total = val_counts.sum()
    # use value count for each category and divide it by the total count of all categories
    # and multiply by 100 to get nice percent values
    df2[col] = val_counts / total * 100

# columns and rows need to be transposed in order to get the result we want  
df2.transpose().plot.bar(stacked=True)
plt.show()