Pandas TypeError: no numeric data to plot [Solved]

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# Pandas TypeError: no numeric data to plot [Solved]

The Pandas "TypeError: no numeric data to plot" occurs when you try to plot a DataFrame but your DataFrame is empty or contains no numeric columns.

To solve the error, make sure your DataFrame is not empty and use the astype() method if you need to convert the values in your columns to numeric.

Here is an example of how the error occurs.

main.py

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import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame({
    'year': [2011, 2014, 2018, 2012, 2025],
    'net_worth': ['5000', '10000', '15000', '10000', '20000'],
    'gdp_per_capita': ['10000', '12000', '15000', '20000', '25000'],
})

print(df[['net_worth', 'gdp_per_capita']].plot())

# ⛔️ TypeError: no numeric data to plot
plt.show()

type error no numeric data to plot

Notice that the values in the columns we tried to call DataFrame.plot are not numeric.

# Use the `astype()` method to convert the values in the columns to numeric

If your DataFrame is not empty, use the DataFrame.astype method to convert the values in the columns you want to plot to numeric.

main.py

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import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame({
    'year': [2011, 2014, 2018, 2012, 2025],
    'net_worth': ['5000', '10000', '15000', '10000', '20000'],
    'gdp_per_capita': ['10000', '12000', '15000', '20000', '25000'],
})

df = df.astype(float)

print(df[['net_worth', 'gdp_per_capita']].plot())

plt.show()

convert column values to numeric before plotting

The code for this article is available on GitHub

Make sure you have the matplotlib module installed to be able to run the code sample.

The DataFrame.astype() method converts the given Pandas object to the specified data type.

You can also call the method on specific DataFrame columns.

main.py

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import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame({
    'year': [2011, 2014, 2018, 2012, 2025],
    'net_worth': ['5000', '10000', '15000', '10000', '20000'],
    'gdp_per_capita': ['10000', '12000', '15000', '20000', '25000'],
})

df['net_worth'] = df['net_worth'].astype(float)
df['gdp_per_capita'] = df['gdp_per_capita'].astype(float)

print(df[['net_worth', 'gdp_per_capita']].plot())

plt.show()

call astype method on specific columns

The code for this article is available on GitHub

Once the values in the columns you want to plot have been converted to numeric, you will be able to call the DataFrame.plot() method without any issues.

You can use the DataFrame.dtypes attribute to verify that the column values are numeric.

main.py

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import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame({
    'year': [2011, 2014, 2018, 2012, 2025],
    'net_worth': ['5000', '10000', '15000', '10000', '20000'],
    'gdp_per_capita': ['10000', '12000', '15000', '20000', '25000'],
})

print(df.dtypes)

df['net_worth'] = df['net_worth'].astype(float)
df['gdp_per_capita'] = df['gdp_per_capita'].astype(float)

print('-' * 50)

print(df.dtypes)

The code for this article is available on GitHub

Running the code sample produces the following output.

shell

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year               int64
net_worth         object
gdp_per_capita    object
dtype: object
--------------------------------------------------
year                int64
net_worth         float64
gdp_per_capita    float64
dtype: object

verify the values are numeric

Accessing the dtypes attribute returns "object" for the two columns before using astype().

After converting the values in the two columns to floating-point numbers, float64 is returned.

# Using the `to_numeric()` method to solve the error

You can also use the pandas.to_numeric() method to solve the error.

main.py

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import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame({
    'year': [2011, 2014, 2018, 2012, 2025],
    'net_worth': ['5000', '10000', '15000', '10000', '20000'],
    'gdp_per_capita': ['10000', '12000', '15000', '20000', '25000'],
})

df['net_worth'] = pd.to_numeric(df['net_worth'])
df['gdp_per_capita'] = pd.to_numeric(df['gdp_per_capita'])

print(df[['net_worth', 'gdp_per_capita']].plot())

plt.show()

The code for this article is available on GitHub

The pandas.to_numeric method converts the given argument to a numeric type.

# Make sure the DataFrame is not empty

You will also get the error if you try to plot an empty DataFrame.

main.py

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import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame({})

df.plot()

# ⛔️ TypeError: no numeric data to plot
plt.show()

trying to plot empty dataframe

The DataFrame has to have at least 1 numeric column for you to be able to use the plot() method.

main.py

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import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame({
    'net_worth': ['5000', '10000', '15000', '10000', '20000'],
})


df['net_worth'] = df['net_worth'].astype(float)

df.plot()

plt.show()

need at least 1 numeric column to be able to plot

The code for this article is available on GitHub

You can also add a column to an empty DataFrame after it has been created.

main.py

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import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame({})


df['net_worth'] = [5000, 10000, 15000, 10000, 20000]


df.plot()

plt.show()

need at least 1 numeric column to be able to plot

I've also written an article on how to add axis labels to a plot in Pandas.

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Pandas TypeError: no numeric data to plot [Solved]

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