I have a data frame that looks something like this and I want am trying to make two grouped bar charts where one is grouped by sex and it shows the counts for the disease for males and females:

This is what ive tried but it shows every datapoint instead of the total counts.

heart_failure_df.set_index(['Sex']).plot(y='disease', kind="bar")

This is ideally what i want:

CodePudding user response：

Chart:

Code:

import pandas as pd
import matplotlib.pyplot as plt

d = {'Age': [23, 43, 32, 51, 29], 
     'Sex': ['m', 'm', 'f', 'f', 'm'],
     'disease': [0, 1, 0, 1, 1]}
df = pd.DataFrame(data=d)

df_pivot = pd.pivot_table(
    df,
    index="Sex",
    columns="disease",
    values="disease",
    aggfunc='count')

fig, ax = plt.subplots()
df_pivot.plot(kind="bar", ax=ax)
ax.legend(["Normal", "Heart Disease"]);
ax.tick_params(axis='x', rotation=0)
ax.set_ylabel("count")

• Pivot puts the dataframe in the correct format to be plotted as grouped bar chart by pd.plot() and counts the occurrences of disease in one step.
• The legend needs to be set manually since in your data disease is '0', '1'.

CodePudding user response：

First formulate your data

s = df.groupby('Sex')['Disease'].count()

After that slice it a little bit

Only males data s['M']

Only females data s['F']

This shall return the series with the wanted y axis and x axis. After that just a simple plot shall do your trick

Just take a look at the documentation (https://matplotlib.org/stable/gallery/lines_bars_and_markers/barchart.html)