are labeled as shown.

Now, we are using loc[] and iloc[] to select a specific row from the DataFrame. Please note that when we select a row using loc[] or iloc[], the returned value is a pandas Series. And as we discussed, loc[] selects a row using its label, where iloc[] selects a row using its index.

series1 = df1.loc["Row 1"]
series2 = df1.iloc[0]
print("series1: \n", series1)
print("series2: \n", series2)

So, the output of the above part of the program will be:

series1: 
Column 1    1
Column 2    2
Column 3    3
Name: Row 1, dtype: int64
series2: 
Column 1    1
Column 2    2
Column 3    3
Name: Row 1, dtype: int64

Next, we are selecting multiple rows from the DataFrame using loc[] and iloc[]. Please note that when we select multiple rows from a DataFrame using loc[] and iloc[], the returned value is a DataFrame. And as we discussed, loc[] selects rows using their labels, where iloc[] selects rows using their indexes.

df2 = df1.loc[["Row 1", "Row 2"]]
df3 = df1.iloc[[0, 1]]
print("df2: \n", df2)
print("df3: \n", df3)

The output of the above part of the program will be:

df2: 
        Column 1  Column 2  Column 3
Row 1         1         2         3
Row 2         4         5         6
df3: 
        Column 1  Column 2  Column 3
Row 1         1         2         3
Row 2         4         5         6

So, the complete output of the given program will be: