1. Slicing with .loc

Slicing Lists

• Slicing is a technique for selecting consecutive elements from objects
• To slice the list, pass the first and last position separated by a colon into square projects

breeds = [“Labrador”, “Poodle”, “Chow Chow”, “Schnauzer”, “Chihuahua”, “St. Bernard”]

breeds[2:5] # 2 refers to the third elements and the 5 is not included in the slice

breeds[:3] # To slice from the beginning of the list, can omit the zero

breeds[ : ] # Slicing with colon on its own returns the whole list

Sort the index before slicing

• To sort the index

dogs_srt = dogs.set_index([“breed”, “color”]).sort_index()

print(dog_srt)

Slicing the outer index level

• To slice rows at the outer level of an index, loc -> passing the first and last values separated by a colon
• Specify index values & final value is included

dogs_str.loc[“Chow Chow” : “Poodle”]

Slicing the inner index level

• The correct approach to slicing at inner index levels is to pass the first and last positions as tuples

dogs.str.loc[(“Labrador”, “Brown”) : (“Schnauzer”, “Grey”)]

• Example:

temperatures_srt = temperatures_ind.sort_index() # Sort the index of temperatures_ind

print(temperatures_srt.loc["Pakistan" : "Russia"]) # Subset rows from Pakistan to Russia

print(temperatures_srt.loc["Lahore" : "Moscow"]) # Subset rows from Lahore to Moscow

print(temperatures_srt.loc[("Pakistan", "Lahore") : ("Russia", "Moscow")]) # Subset rows from Pakistan, Lahore to Russia, Moscow

Slicing columns

• By passing two arguments to loc
• Involves subsetting columns, but keeping all rows
• Pass a colon as the first argument to loc
• The second argument takes column names as the first and last positions to slice on

dogs.str.loc[:, “name” : “height_cm”]

Slicing in both directions

• Slice on rows and columns at the same time

dogs.str.loc[(“Labrador”, “Brown”) : (“Schnauzer”, “Grey”), “name” : “height_cm”]

• Example

print(temperatures_srt.loc[("India", "Hyderabad") : ("Iraq", "Baghdad")]) # Subset rows from India, Hyderabad to Iraq, Baghdad

print(temperatures_srt.loc[:,"date" : "avg_temp_c"]) # Subset columns from date to avg_temp_c

print(temperatures_srt.loc[("India", "Hyderabad") : ("Iraq", "Baghdad"), "date":"avg_temp_c"]) # Subset in both directions at once

Slicing by dates / time series

• Slice dates with the same syntax as other types
• The first and last dates are passed as strings

dogs = dog.set_index(“date_of_birth”).sort_index()

dogs.loc[“2014-08-25” : “2016-09-16”]

• Example

print(temperatures[(temperatures["date"] >= "2010") & (temperatures["date"] < "2012")]) # Use Boolean conditions to subset temperatures for rows in 2010 and 2011

temperatures_ind = temperatures.set_index("date") # Set date as an index

print(temperatures_ind.loc["2010":"2011"]) # Use .loc[] to subset temperatures_ind for rows in 2010 and 2011

print(temperatures_ind.loc["2010-08":"2011-02"]) # Use .loc[] to subset temperatures_ind for rows from Aug 2010 to Feb 2011