CODEWITHSUNDEEP
pythonmatplotlib
IamWarmduscher
IamWarmduscher

Reputation: 955

Matplotlib Bar Graph Error - TypeError: only size-1 arrays can be converted to Python scalars

Suppose I have the following DataFrame:

import pandas as pd
import matplotlib.pyplot as plt
from datetime import datetime as dt

df = pd.DataFrame(
    [
        ['2008-02-19', 10],
        ['2008-03-01', 15],
        ['2009-02-05', 20],
        ['2009-05-10', 40],
        ['2010-10-10', 25],
        ['2010-11-15', 5]
    ],
    columns = ['Date', 'DollarTotal']
)
df

df

I want to plot the total summed by year so I perform the following transformations:

df['Date'] = pd.to_datetime(df['Date'])
df_Year = df.groupby(df['Date'].dt.year)
df_Year = df_Year.sum('DollarTotal')
df_Year

df_Year

The following code in matplotlib creates the chart below:

fig,ax = plt.subplots()
ax.plot(df_Year.index, df_Year.values)
ax.set_xlabel("OrderYear")
ax.set_ylabel("$ Total")
ax.set_title("Annual Purchase Amount")
plt.xticks([x for x in df_Year.index], rotation=0)
plt.show()

plot

The problem occurs when I want to create a bar graph using the same DataFrame. By changing the code above from ax.plot to ax.bar, I get the following error:

error

I've never come across this error before when plotting in matplotlib. What have I done wrong?

Please see the answer below by dm2 which solves this problem.

Edit:

I just figured out why I never had this problem in the past. It has to do with how I summed the groupby. If I replace df_Year = df_Year.sum('DollarTotal') with df_Year = df_Year['DollarTotal'].sum() then this problem does not occur.

df = pd.DataFrame(
    [
        ['2008-02-19', 10],
        ['2008-03-01', 15],
        ['2009-02-05', 20],
        ['2009-05-10', 40],
        ['2010-10-10', 25],
        ['2010-11-15', 5]
    ],
    columns = ['Date', 'DollarTotal']
)
df['Date'] = pd.to_datetime(df['Date'])
df_Year = df.groupby(df['Date'].dt.year)
df_Year = df_Year['DollarTotal'].sum()
df_Year

df_sum

fig,ax = plt.subplots()
ax.bar(df_Year.index, df_Year.values)
ax.set_xlabel("OrderYear")
ax.set_ylabel("$ Total")
ax.set_title("Annual Purchase Amount")
plt.xticks([x for x in df_Year.index], rotation=0)
plt.show()

enter image description here

Upvotes: 2

Views: 3435

Answers (2)

David
David

Reputation: 8298

You could also just use the plot.bar of pandas in the following wat:

df_Year.plot.bar()
plt.show()

This will produce:

enter image description here

Upvotes: 3

dm2
dm2

Reputation: 4275

From matplotlib.axes.Axes.bar documentation, the function expects height parameter to be a scalar or a sequence of scalars. pandas.DataFrame.values is a two-dimensional array that has rows as its first dimension and columns as its second dimension (even with just one column, it's a two dimensional array), so it's a sequence of arrays. Therefore, if you use df.values, you also need to reshape it to the expected sequence (i.e. one-dimensional array) of scalars (i.e. df.values.reshape(len(df))).

Or, specifically in your code: ax.bar(df_Year.index, df_Year.values.reshape(len(df_Year)).

Result:

enter image description here

Upvotes: 7

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