CODEWITHSUNDEEP
pythonpandasmatplotlibrolling-average
meto
meto

Reputation: 3719

Plotting rolling average on top of a stacked bar chart in pandas

I am trying to plot how many daily events of each category happened, together with a 7 days rolling average of the total. Concretely my data has the shape:

date_range = pd.date_range(start='2023-01-01', periods=10)
data = {
    'Category A': np.random.randint(1, 10, 10),
    'Category B': np.random.randint(1, 10, 10),
}
df = pd.DataFrame(data, index=date_range)

adding the rolling average:

df['total'] = df.sum(axis=1)
df['rolling'] = df['total'].rolling(window=7).mean()

Then I thought I could simply do

ax = df[['Category A', 'Category B']].plot(kind='bar', stacked=True)
df['rolling'].plot(kind='line', ax=ax)

However, I can only see the second plot. Is there a way to add one on top of each other, without overwriting the first? alpha does not seem to help here.

Upvotes: 1

Views: 83

Answers (1)

BigBen
BigBen

Reputation: 50008

The x-data for your barplot and line plot don't align. The bar plot has a categorical x-axis, and the bars are at positions 0, 1, 2, .... A quick way to see this is with get_xticks():

ax = df[['Category A', 'Category B']].plot(kind='bar', stacked=True)
ax.get_xticks()

returns

array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])

while

df['rolling'].plot(kind='line', ax=ax)
ax.get_xticks()

returns

array([19358, 19367], dtype=int64)

The easy fix is to specify the x-values manually to align with the barplot:

ax.plot(range(len(df)), df['rolling'])

Upvotes: 1

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