Data Wrangling with Python Datatable - Replicate Pandas’ Map Function

Contents

Data Wrangling with Python Datatable - Replicate Pandas’ Map Function#

Link to Source data #

Task: Create a new column by mapping the values in the city column to the city_state dictionary

from datatable import dt, f

df = dt.Frame({
    "first_name": ["Jason", "Molly", "Tina", "Jake", "Amy"],
    "last_name": ["Miller", "Jacobson", "Ali", "Milner", "Cooze"],
    "age": [42, 52, 36, 24, 73],
    "city": ["San Francisco", "Baltimore", "Miami", "Douglas", "Boston"],
})

city_to_state = {
    "San Francisco": "California",
    "Baltimore": "Maryland",
    "Miami": "Florida",
    "Douglas": "Arizona",
    "Boston": "Massachusetts",
}

df

	first_name	last_name	age	city
	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪
0	Jason	Miller	42	San Francisco
1	Molly	Jacobson	52	Baltimore
2	Tina	Ali	36	Miami
3	Jake	Milner	24	Douglas
4	Amy	Cooze	73	Boston

city_to_state

{'San Francisco': 'California',
 'Baltimore': 'Maryland',
 'Miami': 'Florida',
 'Douglas': 'Arizona',
 'Boston': 'Massachusetts'}

Complete Solution#

m = df["city"]
m.replace(city_to_state)

df["state"] = m
df

	first_name	last_name	age	city	state
	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪
0	Jason	Miller	42	San Francisco	California
1	Molly	Jacobson	52	Baltimore	Maryland
2	Tina	Ali	36	Miami	Florida
3	Jake	Milner	24	Douglas	Arizona
4	Amy	Cooze	73	Boston	Massachusetts

Breakdown of Solution#

Step 1: Create a temporary dataframe to hold the values in city.

m = df['city']
m

	city
	▪▪▪▪
0	San Francisco
1	Baltimore
2	Miami
3	Douglas
4	Boston

Step 2: Replace the values in m with city_to_state, by using the replace function. Note that the replace function does not require assignment, as the computation is done inplace:

m.replace(city_to_state)
m

	city
	▪▪▪▪
0	California
1	Maryland
2	Florida
3	Arizona
4	Massachusetts

Step 3: Assign m to new column state in df:

df["state"] = m
df

	first_name	last_name	age	city	state
	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪
0	Jason	Miller	42	San Francisco	California
1	Molly	Jacobson	52	Baltimore	Maryland
2	Tina	Ali	36	Miami	Florida
3	Jake	Milner	24	Douglas	Arizona
4	Amy	Cooze	73	Boston	Massachusetts

Comments#