Contents

Selecting using .loc[]

Watch it

See the accompanied youtube video at the link here.

Unordered Indexing

Here we have our trusty cereal dataframe.

What would we do if we wanted to select columns and rows that don’t fall consecutively or if we wanted to rearrange them?

cereal
name mfr type calories protein fat sodium ... sugars potass vitamins shelf weight cups rating
0 100% Bran N Cold 70 4 1 130 ... 6 280 25 3 1.0 0.33 68.402973
1 100% Natural Bran Q Cold 120 3 5 15 ... 8 135 0 3 1.0 1.00 33.983679
2 All-Bran K Cold 70 4 1 260 ... 5 320 25 3 1.0 0.33 59.425505
3 All-Bran with Extra Fiber K Cold 50 4 0 140 ... 0 330 25 3 1.0 0.50 93.704912
4 Almond Delight R Cold 110 2 2 200 ... 8 1 25 3 1.0 0.75 34.384843
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
72 Triples G Cold 110 2 1 250 ... 3 60 25 3 1.0 0.75 39.106174
73 Trix G Cold 110 1 1 140 ... 12 25 25 2 1.0 1.00 27.753301
74 Wheat Chex R Cold 100 3 1 230 ... 3 115 25 1 1.0 0.67 49.787445
75 Wheaties G Cold 100 3 1 200 ... 3 110 25 1 1.0 1.00 51.592193
76 Wheaties Honey Gold G Cold 110 2 1 200 ... 8 60 25 1 1.0 0.75 36.187559

77 rows × 16 columns

Let’s say we want only the rows labelled:

  • Clusters (13)

  • Trix (73), and

  • Wheaties (75)

And the columns:

  • name

  • type

  • sugars, and

  • rating

How would we obtain them?

We need to specify each column and row label that we want between square brackets [], that follow .loc[] and we separate the items that we list in the square brackets with commas.

cereal.loc[[13,73,75], ['name', 'type', 'sugars', 'rating']]
name type sugars rating
13 Clusters Cold 7 40.400208
73 Trix Cold 12 27.753301
75 Wheaties Cold 3 51.592193

Ordered Indexing

What if we wanted the rows to be in the order Wheaties (75), Trix (73) and Clusters (13) and columns in the order name, type, rating and sugars.

How would we obtain that?

We would just have to rearranging the order in which we list our rows and columns.

cereal.loc[[75, 73, 13], ['name', 'type', 'rating', 'sugars']]
name type rating sugars
75 Wheaties Cold 51.592193 3
73 Trix Cold 27.753301 12
13 Clusters Cold 40.400208 7

Let’s apply what we learned!

Using my fruit_salad dataframe from earlier…

           name    colour    location    seed   shape  sweetness   water-content  weight
0         apple       red     canada    True   round     True          84         100
1        banana    yellow     mexico   False    long     True          75         120
2    cantaloupe    orange      spain    True   round     True          90        1360
3  dragon-fruit   magenta      china    True   round    False          96         600
4    elderberry    purple    austria   False   round     True          80           5
5           fig    purple     turkey   False    oval    False          78          40
6         guava     green     mexico    True    oval     True          83         450
7   huckleberry      blue     canada    True   round     True          73           5
8          kiwi     brown      china    True   round     True          80          76
9         lemon    yellow     mexico   False    oval    False          83          65

1. If I wanted to make a tropical salad and the recipe calls for kiwi, cantaloupe and guava in this order and I am only interested in columns ordered as sweetness, weight, seed and location, what would my code look like?
a) fruit_salad.loc[8, 2, 6:"sweetness", "weight", "seed", "location"]
b) fruit_salad.loc[[8, 2, 6]:["sweetness", "weight", "seed", "location"]]
c) fruit_salad.loc[[8, 2, 6], ["sweetness", "weight", "seed", "location"]]
d) fruit_salad.loc[[2, 6, 8], ["location", "seed”, “sweetness", "weight"]]

Solutions!

  1. c) fruit_salad.loc[[8, 2, 6], ["sweetness", "weight", "seed", "location"]]