Sorting and subsetting
Data Manipulation with pandas
Richie Cotton
Data Evangelist at DataCamp
Sorting
dogs.sort_values("weight_kg")
name breed color height_cm weight_kg date_of_birth
5 Stella Chihuahua Tan 18 2 2015-04-20
3 Cooper Schnauzer Gray 49 17 2011-12-11
0 Bella Labrador Brown 56 24 2013-07-01
1 Charlie Poodle Black 43 24 2016-09-16
2 Lucy Chow Chow Brown 46 24 2014-08-25
4 Max Labrador Black 59 29 2017-01-20
6 Bernie St. Bernard White 77 74 2018-02-27
Sorting in descending order
dogs.sort_values("weight_kg", ascending=False)
name breed color height_cm weight_kg date_of_birth
6 Bernie St. Bernard White 77 74 2018-02-27
4 Max Labrador Black 59 29 2017-01-20
0 Bella Labrador Brown 56 24 2013-07-01
1 Charlie Poodle Black 43 24 2016-09-16
2 Lucy Chow Chow Brown 46 24 2014-08-25
3 Cooper Schnauzer Gray 49 17 2011-12-11
5 Stella Chihuahua Tan 18 2 2015-04-20
Sorting by multiple variables
dogs.sort_values(["weight_kg", "height_cm"])
name breed color height_cm weight_kg date_of_birth
5 Stella Chihuahua Tan 18 2 2015-04-20
3 Cooper Schnauzer Gray 49 17 2011-12-11
1 Charlie Poodle Black 43 24 2016-09-16
2 Lucy Chow Chow Brown 46 24 2014-08-25
0 Bella Labrador Brown 56 24 2013-07-01
4 Max Labrador Black 59 29 2017-01-20
6 Bernie St. Bernard White 77 74 2018-02-27
Sorting by multiple variables
dogs.sort_values(["weight_kg", "height_cm"], ascending=[True, False])
name breed color height_cm weight_kg date_of_birth
5 Stella Chihuahua Tan 18 2 2015-04-20
3 Cooper Schnauzer Gray 49 17 2011-12-11
0 Bella Labrador Brown 56 24 2013-07-01
2 Lucy Chow Chow Brown 46 24 2014-08-25
1 Charlie Poodle Black 43 24 2016-09-16
4 Max Labrador Black 59 29 2017-01-20
6 Bernie St. Bernard White 77 74 2018-02-27
pandas with relevant values highlighted: Bella, Lucy and Charlie in descending order by height
Subsetting columns
dogs["name"]
0 Bella
1 Charlie
2 Lucy
3 Cooper
4 Max
5 Stella
6 Bernie
Name: name, dtype: object
Subsetting multiple columns
dogs[["breed", "height_cm"]]
breed height_cm
0 Labrador 56
1 Poodle 43
2 Chow Chow 46
3 Schnauzer 49
4 Labrador 59
5 Chihuahua 18
6 St. Bernard 77
cols_to_subset = ["breed", "height_cm"]
dogs[cols_to_subset]
breed height_cm
0 Labrador 56
1 Poodle 43
2 Chow Chow 46
3 Schnauzer 49
4 Labrador 59
5 Chihuahua 18
6 St. Bernard 77
Subsetting rows
dogs["height_cm"] > 50
0 True
1 False
2 False
3 False
4 True
5 False
6 True
Name: height_cm, dtype: bool
Subsetting rows
dogs[dogs["height_cm"] > 50]
name breed color height_cm weight_kg date_of_birth
0 Bella Labrador Brown 56 24 2013-07-01
4 Max Labrador Black 59 29 2017-01-20
6 Bernie St. Bernard White 77 74 2018-02-27
Subsetting based on text data
dogs[dogs["breed"] == "Labrador"]
name breed color height_cm weight_kg date_of_birth
0 Bella Labrador Brown 56 24 2013-07-01
4 Max Labrador Black 59 29 2017-01-20
Subsetting based on dates
dogs[dogs["date_of_birth"] < "2015-01-01"]
name breed color height_cm weight_kg date_of_birth
0 Bella Labrador Brown 56 24 2013-07-01
2 Lucy Chow Chow Brown 46 24 2014-08-25
3 Cooper Schnauzer Gray 49 17 2011-12-11
Subsetting based on multiple conditions
is_lab = dogs["breed"] == "Labrador"is_brown = dogs["color"] == "Brown"dogs[is_lab & is_brown]
name breed color height_cm weight_kg date_of_birth
0 Bella Labrador Brown 56 24 2013-07-01
dogs[ (dogs["breed"] == "Labrador") & (dogs["color"] == "Brown") ]
Subsetting using .isin()
is_black_or_brown = dogs["color"].isin(["Black", "Brown"])
dogs[is_black_or_brown]
name breed color height_cm weight_kg date_of_birth
0 Bella Labrador Brown 56 24 2013-07-01
1 Charlie Poodle Black 43 24 2016-09-16
2 Lucy Chow Chow Brown 46 24 2014-08-25
4 Max Labrador Black 59 29 2017-01-20
Let's practice!
Data Manipulation with pandas
