How to get row number in dataframe in Pandas?

How can I get the number of the row in a dataframe that contains a certain value in a certain column using Pandas? For example, I have the following dataframe:

     ClientID  LastName
0    34        Johnson
1    67        Smith
2    53        Brows  

How can I find the number of the row that has 'Smith' in 'LastName' column?

To get all indices that matches 'Smith'

>>> df[df['LastName'] == 'Smith'].index
Int64Index([1], dtype='int64')

or as a numpy array

>>> df[df['LastName'] == 'Smith'].index.to_numpy()  # .values on older versions
array([1])

or if there is only one and you want the integer, you can subset

>>> df[df['LastName'] == 'Smith'].index[0]
1

You could use the same boolean expressions with .loc, but it is not needed unless you also want to select a certain column, which is redundant when you only want the row number/index.

df.index[df.LastName == 'Smith']

Or

df.query('LastName == "Smith"').index

Will return all row indices where LastName is Smith

Int64Index([1], dtype='int64')

df.loc[df.LastName == 'Smith']

will return the row

    ClientID    LastName
1   67          Smith

and

df.loc[df.LastName == 'Smith'].index

will return the index

Int64Index([1], dtype='int64')

NOTE: Column names 'LastName' and 'Last Name' or even 'lastname' are three unique names. The best practice would be to first check the exact name using df.columns. If you really need to strip the column names of all the white spaces, you can first do

df.columns = [x.strip().replace(' ', '') for x in df.columns]

 len(df[df["Lastname"]=="Smith"].values)