CODEWITHSUNDEEP
pythonpandas
user6882757
user6882757

Reputation:

ValueError: Columns must be same length as key in pandas

i have df below 

    Cost,Reve
    0,3
    4,0
    0,0
    10,10
    4,8

len(df['Cost']) = 300

len(df['Reve']) = 300

I need to divide df['Cost'] / df['Reve']

Below is my code

df[['Cost','Reve']] = df[['Cost','Reve']].apply(pd.to_numeric)

I got the error ValueError: Columns must be same length as key

df['C/R'] = df[['Cost']].div(df['Reve'].values, axis=0)

I got the error ValueError: Wrong number of items passed 2, placement implies 1

Upvotes: 7

Views: 38033

Answers (3)

9Morgan8
9Morgan8

Reputation: 61

I had the same error, but it did not come from the above two issues. In my case the columns had the same length. What helped me was transforming my Series to a DataFrame with pd.DataFrame() and then assigning its values to a new column of my existing df.

Upvotes: 1

Mohit Gaikwad
Mohit Gaikwad

Reputation: 340

The issue lies in the size of data that you are trying to assign to the columns. I had an issue with this:

df[['X1','X2', 'X3']] = pd.DataFrame(df.X.tolist(), index= df.index)

I was trying to assign values of X to 3 columns X1,X2,X3, assuming that X has 3 values, but, X had 4 values.

So the revised code in my case was

df[['X1','X2', 'X3','X4']] = pd.DataFrame(df.X.tolist(), index= df.index)

Upvotes: 0

jezrael
jezrael

Reputation: 862481

Problem is duplicated columns names, verify:

#generate duplicates
df = pd.concat([df, df], axis=1)
print (df)
  Cost Reve Cost Reve
0    0    3    0    3
1    4    0    4    0
2    0    0    0    0
3   10   10   10   10
4    4    8    4    8

df[['Cost','Reve']] = df[['Cost','Reve']].apply(pd.to_numeric)
print (df)
# ValueError: Columns must be same length as key

You can find this columns names:

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

If same values in columns is possible remove duplicated by:

df = df.loc[:, ~df.columns.duplicated()]
df[['Cost','Reve']] = df[['Cost','Reve']].apply(pd.to_numeric)

#simplify division
df['C/R'] = df['Cost'].div(df['Reve'])
print (df)
   Cost  Reve  C/R
0     0     3  0.0
1     4     0  inf
2     0     0  NaN
3    10    10  1.0
4     4     8  0.5

Upvotes: 12

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