Filtering String/float/integer Values In Pandas Dataframe Columns

How can I filter only string values/ integer/ float values in one column (SIC) in a pandas data frame like below? SIC 1 246804 2

Solution 1:

You can use the outputs from pd.to_numeric and boolean indexing.

To get only the strings use:

df[pd.to_numeric(df.SIC, errors='coerce').isnull()]

Output:

      SIC
5   shine
6add8     Nan
9string

To get only the numbers use:

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

Output:

        SIC
1    246804
2    135272
3    898.01
4   3453.33
7       522
10    29.11
11       20

Solution 2:

You can use the apply() method along with the isinstance() function. Can replace str with int, float, etc:

df = pd.DataFrame([1,2,4.5,np.NAN,'asdf',5,'string'],columns=['SIC'])
print(df)
      SIC
0       1
1       2
2     4.5
3     NaN
4    asdf
5       5
6  string

print(df[df['SIC'].apply(lambda x: isinstance(x,str))])
      SIC
4    asdf
6  string