[FIXED] Data presentation difference in python

Issue

Hopefully a fairly simple answer to my issue.

When I run the following code:

print (data_1.iloc[1])

I get a nice, vertical presentation of the data, with each column value header, and its value presented on separate rows. This is very useful when looking at 2 sets of data, and trying to find discrepancies.

However, when I write the code as:

print (data_1.loc[data_1["Name"].isin(["John"])])

I get all the information arrayed across the screen, with the column header in 1 row, and the values in another row.

My question is: Is there any way of using the second code, and getting the same vertical presentation of the data?

Solution

The difference is that data_1.iloc[1] returns a pandas Series whereas data_1.loc[data_1["Name"].isin(["John"])] returns a DataFrame. Pandas has different representations for these two data types (i.e. they print differently).

The reason iloc[1] gives you a Series is because you indexed it using a scalar. If you do data_1.iloc[[1]] you'll see you get a DataFrame instead. Conversely, I'm assuming that data_1["Name"].isin(["John"]) is returning a collection. If you wanted to get a Series instead you might try something like

print(data_1.loc[data_1["Name"].isin(["John"])[0]])

but only if you're sure you're getting one element back.

Answered By - Dan