Sort dataframe by string length

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.

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

Using DataFrame.sort_values with key argument since pandas >= 1.1.0:

We can now pas the length of the string or any other custom key in the sort_values method:

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

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)