How to Remove Rows from Pandas Data Frame that Contains any String in a Particular Column

Question

I have CSV data in the following format:

+-------------+-------------+-------+
|  Location   | Num of Reps | Sales |
+-------------+-------------+-------+
| 7589         


        

Answer 1

You can use pd.to_numeric to coerce non numeric values to nan and then filter based on if the Location is nan:

df[pd.to_numeric(df.Location, errors='coerce').notnull()]

#Location  Num of Reps  Sales
#0  75894            3     12
#2  75286            7     24
#4  27659            3     17

Answer 2

In [139]: df[~df.Location.str.contains('\D')]
Out[139]:
  Location  Num of Reps  Sales
0    75894            3     12
2    75286            7     24
4    27659            3     17

Answer 3

Or you could do

df[df['Location'].str.isnumeric()]

  Location  Num of Reps  Sales
0    75894            3     12
2    75286            7     24
4    27659            3     17

Answer 4

df[df['Location'].str.isdigit()]


  Location  Num of Reps  Sales
0    75894            3     12
2    75286            7     24
4    27659            3     17