When you are working with data manipulation and analysis in Python, you may encounter an error message “ValueError: Cannot insert level_0, already exists“.
This error is commonly encountered when trying to merge or concatenate pandas DataFrame objects that have the same column names or hierarchical indexes.
Understanding the ValueError
The “ValueError: Cannot insert level_0, already exists” occurs when we attempt to combine multiple DataFrames, and there are duplicate column names or hierarchical indexes in the data.
How the Error Occurs?
This is an example code of how the error occurs:
import pandas
person = pandas.DataFrame({
'name': ['jude', 'glenn', 'caren', 'eliver'],
'sample': range(10,14),
})
person = person.reset_index()
person = person.reset_index()
person = person.reset_index()Output:
Traceback (most recent call last):
File “C:\Users\Dell\PycharmProjects\Python-Code-Example\main.py”, line 8, in
person = person.reset_index()
File “C:\Users\Dell\PycharmProjects\Python-Code-Example\venv\lib\site-packages\pandas\core\frame.py”, line 6219, in reset_index
new_obj.insert(
File “C:\Users\Dell\PycharmProjects\Python-Code-Example\venv\lib\site-packages\pandas\core\frame.py”, line 4782, in insert
raise ValueError(f”cannot insert {column}, already exists”)
ValueError: cannot insert level_0, already exists
How to Solve the Valueerror: cannot insert level_0 already exists?
Here are the following solutions that you can apply to fix the Valueerror cannot insert level_0 already exists.
Solution 1 : Using Drop Option
To fix this valueerror we can use a drop option method. This drops an existing index with the same name and replaces it with the new, reset index.
Here’s an example code:
import pandas
person = pandas.DataFrame({
'name': ['jude', 'glenn', 'caren', 'eliver'],
'sample': range(10,14),
})
person = person.reset_index(drop=True)
person = person.reset_index(drop=True)
person = person.reset_index(drop=True)Solution 2: Renaming the Columns
One of the solutions to resolve the valueerror is to rename the columns before merging or concatenating the DataFrames.
This is to ensure that it have a different column names and prevents the ValueError.
Here’s an example code:
import pandas as pd
value_example1 = pd.DataFrame({'X': [1, 2, 3], 'Y': [4, 5, 6]})
value_example2 = pd.DataFrame({'X': [7, 8, 9], 'Y': [10, 11, 12]})
# Rename columns to make them unique
value_example1.columns = ['X_value_example1', 'Y_value_example2']
value_example2.columns = ['X_value_example2', 'Y_value_example2']
# Concatenate the DataFrames
sample_result = pd.concat([value_example1, value_example2], axis=1)
print(sample_result)Output:
By renaming the columns to ‘X_value_example1‘, ‘Y_value_example2‘, ‘X_value_example2‘, and ‘Y_value_example2‘, we can ensure differences and successfully concatenate the DataFrames.
Solution 3: Using reset_index() Function
Another way to solve the valueerror is to reset the index of the DataFrames before merging them.
This can be done using the reset_index() method.
Here’s an example code:
import pandas as pd
value_example1 = pd.DataFrame({'X': [1, 2, 3], 'Y': [4, 5, 6]})
value_example2 = pd.DataFrame({'X': [7, 8, 9], 'Y': [10, 11, 12]})
value_example1.reset_index(drop=True, inplace=True)
value_example2.reset_index(drop=True, inplace=True)
sample_result = pd.concat([value_example1, value_example2], axis=1)
print(sample_result)Output:
By resetting the index of both DataFrames using the reset_index() method, we can remove the possibility of duplicate indexes, which resolves the ValueError.
Conclusion
The “ValueError: Cannot insert level_0, already exists” is a common error encountered when we are merging or concatenating pandas DataFrames with duplicate column names or hierarchical indexes.
In this article, we have discussed an example code that triggers this value error and provided three solutions to resolve it: Using Drop Option, renaming columns, and resetting the index.
By following these solutions in this article, you can prevent the ValueError and successfully combine your DataFrames.