ValueError: Length of values does not match length of index

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# ValueError: Length of values does not match length of index

The Pandas "ValueError: Length of values (X) does not match length of index (Y)" occurs when you try to assign a column of a NumPy array of a different length to a DataFrame.

To solve the error, use a Series instead of a NumPy array.

Here is an example of how the error occurs.

main.py

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import pandas as pd

df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': [4, 5, 6],
    'C': [7, 8, 9]
})

#    A  B  C
# 0  1  4  7
# 1  2  5  8
# 2  3  6  9
print(df)

df['D'] = [10, 11]

# ⛔️ ValueError: Length of values (2) does not match length of index (3)
print(df)

value error length of values does not match length of index

Each column has 3 rows in the example, but we tried adding a new column that only contains 2 elements.

The error is also caused if you try to assign a column that points to a NumPy array of a different length.

main.py

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import pandas as pd
import numpy as np

df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': [4, 5, 6],
    'C': [7, 8, 9]
})

#    A  B  C
# 0  1  4  7
# 1  2  5  8
# 2  3  6  9
print(df)

df['D'] = np.array([10, 11])

# ⛔️ ValueError: Length of values (2) does not match length of index (3)
print(df)

The NumPy array only has 2 elements but each column in the DataFrame has 3 rows, so it is expected that the NumPy array should also have 3 elements.

# Solve the error by using a Pandas Series

You can solve the error by using a pandas Series instead of a list or a NumPy array.

main.py

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import pandas as pd

df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': [4, 5, 6],
    'C': [7, 8, 9]
})


df['D'] = pd.Series([10, 11])

#    A  B  C     D
# 0  1  4  7  10.0
# 1  2  5  8  11.0
# 2  3  6  9   NaN
print(df)

using pandas series instead of numpy array

The code for this article is available on GitHub

The pandas.Series class is used to create a one-dimensional ndarray with axis labels.

However, notice that we have a NaN value because the Series only has 2 elements whereas each column in the DataFrame has 3 rows.

If you need to replace the NaN values in the DataFrame with zeros, use the DataFrame.fillna() method.

main.py

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import pandas as pd

df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': [4, 5, 6],
    'C': [7, 8, 9]
})


df['D'] = pd.Series([10, 11])

df = df.fillna(0)

#    A  B  C     D
# 0  1  4  7  10.0
# 1  2  5  8  11.0
# 2  3  6  9   0.0
print(df)

replace nan with zero in dataframe

The code for this article is available on GitHub

The DataFrame.fillna() method fills NA/NaN with the supplied value.

You can also pass the inplace argument when calling fillna() to avoid reassigning the variable.

main.py

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import pandas as pd

df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': [4, 5, 6],
    'C': [7, 8, 9]
})


df['D'] = pd.Series([10, 11])

df.fillna(0, inplace=True)

#    A  B  C     D
# 0  1  4  7  10.0
# 1  2  5  8  11.0
# 2  3  6  9   0.0
print(df)

If the inplace argument is set to True, then the DataFrame is filled in-place.

When the argument is set to True, the original DataFrame object is mutated and None is returned.

# Incorrectly creating a `DataFrame` or a `Series`

The error also occurs when you incorrectly try to create a DataFrame or a Series.

Here is an example.

main.py

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import pandas as pd

# ⛔️ ValueError: Length of values (2) does not match length of index (3)
df = pd.DataFrame({
    'A': [1, 2],
    'B': [3, 4],
    'C': [5, 6]
}, index=['X', 'Y', 'Z'])

Each column in the DataFrame has 2 rows (values), however, we specified 3 values in the index list.

To solve the error, we have to only specify 2 values in the index list or add a row to each column (A, B and C).

main.py

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import pandas as pd

df = pd.DataFrame({
    'A': [1, 2],
    'B': [3, 4],
    'C': [5, 6]
}, index=['X', 'Y'])

#    A  B  C
# X  1  3  5
# Y  2  4  6
print(df)

The code for this article is available on GitHub

Now each column in the DataFrame has 2 rows and the index contains 2 items, so the issue is resolved.

You might also encounter the error when creating a Series.

main.py

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import pandas as pd

# ⛔️ ValueError: Length of values (3) does not match length of index (2)
series = pd.Series(
    [1, 2, 3],
    name='ser',
    index=['A', 'B']
)

The list we passed to the pandas.Series() constructor contains 3 elements, however, the index list only contains 2.

To solve the error, make sure the index list also has 3 elements.

main.py

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import pandas as pd

series = pd.Series(
    [1, 2, 3],
    name='ser',
    index=['A', 'B', 'C']
)

# A    1
# B    2
# C    3
# Name: ser, dtype: int64
print(series)

The code for this article is available on GitHub

Now the list we passed to the pandas.Series class contains 3 elements and the index list also contains 3 elements, so everything works as expected.

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ValueError: Length of values does not match length of index

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