Pandas: Handling Dataframes

Question

A certain dataframe, has a similar break with the one below:

import pandas as pd

df = pd.DataFrame({'name': ['John', 'Elvis', 'Gerrard', 'Pitty'],
              'age': [22,23,24,25],
              'document': [111,222,333,4444]})

How can I make a filter to return only the rows where the values ​​in the document column are only 3 digits?

Answer 1

log

df.query('2 <= log10(document) < 3')

      name  age  document
0     John   22       111
1    Elvis   23       222
2  Gerrard   24       333

---

Expanded example

df = pd.DataFrame({
    'name': ['John', 'Elvis', 'Gerrard', 'Pitty'],
    'age': [22, 23, 24, 25],
    'document': [11, 222, 999, 1000]
})

df

      name  age  document
0     John   22        11  # 2 digit number
1    Elvis   23       222  # 3 digit number
2  Gerrard   24       999  # 3 digit number | edge case
3    Pitty   25      1000  # 4 digit number | edge case

Let's get only 3 digit numbers

df.query('2 <= log10(document) < 3')

      name  age  document
1    Elvis   23       222
2  Gerrard   24       999

Answer 2

Try // which will return the divisor of 1000, since 3 digit so the divisor should be 0

df[df.document//1000==0]
Out[474]: 
      name  age  document
0     John   22       111
1    Elvis   23       222
2  Gerrard   24       333

---

We convert to str then count the len

df[df.document.astype(str).str.len().eq(3)]
Out[476]: 
      name  age  document
0     John   22       111
1    Elvis   23       222
2  Gerrard   24       333

Update

df[df.document.astype(str).str.split('.').str[0].str.len().eq(3)]

Answer 3

df[df.document.apply(lambda x: len(str(x)) == 3)]

Answer 4

This will work for positive and negative numbers in the document column:

df[df['document'].abs().astype(str).str.len() == 3]