One error you may encounter when using pandas is:
ValueError: Index contains duplicate entries, cannot reshape
This error usually occurs when you attempt to reshape a pandas DataFrames by using the pivot() function, but there are multiple values in the resulting DataFrame that share the same index values.
The following example shows how to fix this error in practice.
How to Reproduce the Error
Suppose we have the following pandas DataFrame:
import pandas as pd #create DataFrame df = pd.DataFrame({'team': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'], 'position': ['G', 'G', 'F', 'F', 'G', 'G', 'F', 'F'], 'points': [5, 7, 7, 9, 4, 9, 9, 12]}) #view DataFrame df team position points 0 A G 5 1 A G 7 2 A F 7 3 A F 9 4 B G 4 5 B G 9 6 B F 9 7 B F 12
Now suppose we attempt to pivot the DataFrame, using team as the rows and position as the columns:
#attempt to reshape DataFrame
df.pivot(index='team', columns='position', values='points')
ValueError: Index contains duplicate entries, cannot reshape
We receive an error because there are multiple rows in the DataFrame that share the same values for team and position.
Thus, when we attempt to reshape the DataFrame, pandas doesn’t know which points value to display in each cell in the resulting DataFrame.
How to Fix the Error
To fix this error, we can use the pivot_table() function with a specific aggfunc argument to aggregate the data values in a certain way.
For example, we can use pivot_table() to create a new DataFrame that uses team as the rows, position as the columns, and the sum of the points values in the cells of the DataFrame:
df.pivot_table(index='team', columns='position', values='points', aggfunc='sum')
position F G
team
A 16 12
B 21 13
Notice that we don’t receive an error this time.
The values in the DataFrame show the sum of points for each combination of team and position.
Note that we could also use a different value for aggfunc, such as the mean:
df.pivot_table(index='team', columns='position', values='points', aggfunc='mean')
position F G
team
A 8.0 6.0
B 10.5 6.5
By using the aggfunc argument within the pivot_table() function, we’re able to avoid any errors.
Note: You can find the complete documentation for the pivot_table() function here.
Additional Resources
The following tutorials explain how to fix other common errors in Python:
How to Fix KeyError in Pandas
How to Fix: ValueError: cannot convert float NaN to integer
How to Fix: ValueError: operands could not be broadcast together with shapes