Ideal Solutions to Fix “Reindexing only valid with uniquely valued Index objects” error

Python is a famous programming language that has been used for designing various applications. Being a renowned one in the world of programming, every new programmer also wants to learn it. When you are working with Python, “reindexing only valid with uniquely valued Index objects” error can show up that can make you worried. There is no need to worry as we are here to guide you about the error and how it occurs.

If you ever encounter an error warning at the end of your code, then you can solve it with the method we are going to discuss in the post. But, first, understand how the error occurs

How Does “Reindexing only valid with uniquely valued Index objects” Error Occurs?

Let’s suppose you have a dataframe with the name ‘df1’

df1:

  Group  Name
0     A   nick
1     B   mike
2     C   pope
3     A   max
4     C   chris

df1:

With a schedule dataframe named ‘df2’

df2:

      Group     Due_Date      Assignment
0     A         1-20 18:30    Query #0 A
1     B         1-22 17:00    Query #0 A
2     C         1-22 17:00    Query #0 A
5     A         1-25 12:00    Test A
6     B         1-25 12:00    Test A
7     C         1-25 13:00    Test A

You must be pivoted df2 to keep the assignment in the column ‘df2’ put

df2 = df2.pivot(index='Group',
         columns='Assignment',
         values='Due_Date')
df2_pivoted:

Assignment      Test A   Query #0 A
Group
A           1-25 12:00  1-20 18:30
B           1-25 12:00  1-22 17:00
C           1-25 13:00  1-22 17:00

You get the error warning when you try to add the name like this:

d1=df1.set_index('Group')['Name']
p1='({})'.format('\b|\b'.join(df1['Group']))
df4['Name']=df4['Group'].str.extract(p1,expand=False).map(d1)

And here you end up with

reindexing only valid with uniquely valued Index objects

Solutions To fix ‘reindexing only valid with uniquely valued Index objects’ error

Now that you have seen how you end up with the error warning. You must be looking to have an output like this

df2_final:
Group      Name      Test A       Query #0 A
A          nick       1-25 12:00   1-20 18:30
B          mike       1-25 12:00   1-22 17:00
C          pope       1-25 13:00   1-22 17:00
A          max        1-25 12:00   1-20 18:30
C          chris      1-25 13:00   1-22 17:00

To get this in return, you need to follow the solutions below

Solution 1 – Avoid Duplicate Column names

The error can show up in the output because of the same data you are working on. Your data needs to be modified to fix the error because of the duplicate column names

df2 = pd.DataFrame({'col0': [0,1,2],
'col1': [3,4,5]
}).rename(columns={'col1':'col0'})
print (df2)
col0 col0 <- col0 is duplicated
0 0 3
1 1 4
2 2 5

df3 = pd.DataFrame({'col0': [6,7,8],
'col1': ['9','10','11'],
'col2': ['12','13','14']
})

# Join and keep columns from df2

df4 = pd.concat([df2, df3], ignore_index=True).reindex(df2.columns, axis='columns')
print (df4)

here, you land up in reindexing error. Check the below

print (df2.columns[df2.columns.duplicated(keep=False)])
Index(['col0', 'col0'], dtype='object')

print (df3.columns[df3.columns.duplicated(keep=False)])
Index([], dtype='object')

You found the issue duplication here. Now, the process of deduplicating them can solve the error.

print (pd.io.parsers.ParserBase({'names':df2.columns})._maybe_dedup_names(df2.columns))
['col0', 'col0.1']

Solution 2 – Pivot df2 and df4 with df2_pivoted

Panda is a Python Library that is known to analyze your data. The cause of the error is Panda as it is unable to handle assigned names. Let’s take a look at the example to understand it better

df4:
Group   Name
A       nick
B       mike
C       pope
A       max
C       chris

You should try this code to solve the issue:

df4.set_index('Group', inplace=True)
df2_pivoted = df2_pivoted.join(df4, how='left')

Conclusion

So, finally, you find the solutions to fix the “Reindexing only valid with uniquely valued Index objects” error. Hope you find it helpful!