Sort dataframe by string length

Question

I want to sort by name length. There doesn't appear to be a key parameter for sort_values so I'm not sure how to accomplish this. Here is a test df:

import pandas as pd
df = pd.DataFrame({'name': ['Steve', 'Al', 'Markus', 'Greg'], 'score': [2, 4, 2, 3]})

Glower

Possible duplicate of sort dataframe by length of string in a column – Potential

@jezrael Please read my reason. I mentioned it explicitly: #46177862 – Potential

There are more options there. If not, you can edit this answer and include all those other solutions. – Potential

Answer 1

You can use reindex of index of Series created by len with sort_values:

print (df.name.str.len())
0    5
1    2
2    6
3    4
Name: name, dtype: int64

print (df.name.str.len().sort_values())
1    2
3    4
0    5
2    6
Name: name, dtype: int64

s = df.name.str.len().sort_values().index
print (s)
Int64Index([1, 3, 0, 2], dtype='int64')

print (df.reindex(s))
     name  score
1      Al      4
3    Greg      3
0   Steve      2
2  Markus      2

---

df1 = df.reindex(s)
df1 = df1.reset_index(drop=True)
print (df1)
     name  score
0      Al      4
1    Greg      3
2   Steve      2
3  Markus      2

Ashworth

Great answer, I tried this approach with lists too (Sorting a DataFrame by list length), since .str.len() works with lists as mentioned in the question Pythonic way for calculating length of lists in pandas dataframe column in this link – Mcmahan

This is clever, but you should note it's only safe to do when it's ok to trash the existing index. – Lynx

Answer 2

Using DataFrame.sort_values we can pass an anonymous (lambda) function computing string length (using .str.len() Series method) to the key argument:

df = pd.DataFrame({
    'name': ['Steve', 'Al', 'Markus', 'Greg'], 
    'score': [2, 4, 2, 3]
})
print(df)

     name  score
0   Steve      2
1      Al      4
2  Markus      2
3    Greg      3

df.sort_values(by="name", key=lambda x: x.str.len())

     name  score
1      Al      4
3    Greg      3
0   Steve      2
2  Markus      2

Kaylil

Thanks. Just in case someone needs to lower case and sort df.sort_index(key=lambda x: x.str.lower().str.len()) – Seward

Answer 3

I found this solution more intuitive, specially if you want to do something depending on the column length later on.

df['length'] = df['name'].str.len()
df.sort_values('length', ascending=False, inplace=True)

Now your dataframe will have a column with name length with the value of string length from column name in it and the whole dataframe will be sorted in descending order.

Trover

This should be the accepted answer. Much simpler and easily reused. – Backgammon

Answer 4

The answer of @jezrael is great and explains well. Here is the final result :

index_sorted = df.name.str.len().sort_values(ascending=True).index
df_sorted = df.reindex(index_sorted)
df_sorted = df_sorted.reset_index(drop=True)

Preoccupy

Answer 5

A fancy and minimal solution:

df.iloc[df.agg({"name":len}).sort_values('name').index]



     name  score
1      Al      4
3    Greg      3
0   Steve      2
2  Markus      2

Leopold

Nice one! thanxx !! – Fango

Answer 6

It's worth using the key argument to avoid creating unnecessary columns:

df.sort_values("column_name", ascending=True, key=lambda col: col.str.len())

Onepiece