Use np.repeat:

Version 1:

Try using np.repeat:

newdf = pd.DataFrame(np.repeat(df.values, 3, axis=0))
newdf.columns = df.columns
print(newdf)

The above code will output:

  Person   ID ZipCode  Gender
0  12345  882   38182  Female
1  12345  882   38182  Female
2  12345  882   38182  Female
3  32917  271   88172    Male
4  32917  271   88172    Male
5  32917  271   88172    Male
6  18273  552   90291  Female
7  18273  552   90291  Female
8  18273  552   90291  Female

np.repeat repeats the values of df, 3 times.

Then we add the columns with assigning new_df.columns = df.columns.

Version 2:

You could also assign the column names in the first line, like below:

newdf = pd.DataFrame(np.repeat(df.values, 3, axis=0), columns=df.columns)
print(newdf)

The above code will also output:

  Person   ID ZipCode  Gender
0  12345  882   38182  Female
1  12345  882   38182  Female
2  12345  882   38182  Female
3  32917  271   88172    Male
4  32917  271   88172    Male
5  32917  271   88172    Male
6  18273  552   90291  Female
7  18273  552   90291  Female
8  18273  552   90291  Female