Tested in python 3.11, pandas 1.5.1, matplotlib 3.6.2 Sample Data and Imports import pandas as pd import matplotlib.pyplot as plt import numpy as np np.random.seed(2022) # creates a consistent sample y = np.random.rand(10,4) y[:,0]= np.arange(10) df = pd.DataFrame(y, columns=[“X”, “A”, “B”, “C”]) X A B C 0 0.0 0.499058 0.113384 0.049974 1 1.0 0.486988 0.897657 … Read more
Are you getting errors, or just not sure where to start? %pylab inline import pandas as pd import matplotlib.pyplot as plt df2 = df.groupby([‘Name’, ‘Abuse/NFF’])[‘Name’].count().unstack(‘Abuse/NFF’).fillna(0) df2[[‘abuse’,’nff’]].plot(kind=’bar’, stacked=True)
Since this question asked for a stacked bar chart in Seaborn and the accepted answer uses pandas, I thought I’d give an alternative approach that actually uses Seaborn. Seaborn gives an example of a stacked bar but it’s a bit hacky, plotting the total and then overlaying bars on top of it. Instead, you can … Read more
Imports and DataFrame import pandas as pd import matplotlib.pyplot as plt data = {‘var’: [‘TR’, ‘AC’, ‘F&B’], ‘2019 1Q’: [6600, 1256, 588], ‘2019 2Q’: [6566, 1309, 586], ‘2019 3Q’: [7383, 1525, 673]} df = pd.DataFrame(data) df.set_index(‘var’, inplace=True) # display(df) 2019 1Q 2019 2Q 2019 3Q var TR 6600 6566 7383 AC 1256 1309 1525 F&B … Read more