Data Wrangling with Python Datatable - Conditional Statements

Transformation based on a Single Condition

Source data

Task: if c is positive, then value should be a - b, else b - a.

from datatable import dt, f, update, ifelse

df = dt.Frame({"a": [1, 1, 2, 4], "b": [2, 2, 3, 2], "c": [3, -3, 2, -1]})
df

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Cell In[1], line 1
----> 1 from datatable import dt, f, update, ifelse
      2 
      3 df = dt.Frame({"a": [1, 1, 2, 4], "b": [2, 2, 3, 2], "c": [3, -3, 2, -1]})
      4 df

File /opt/hostedtoolcache/Python/3.11.17/x64/lib/python3.11/site-packages/datatable/__init__.py:181
    178 del datatable
    180 # This will run only in Jupyter notebook
--> 181 init_styles()
    183 options = dt.options.Config(options={}, prefix="")
    184 dt.lib._datatable.initialize_options(options)

AttributeError: module 'IPython.core.display' has no attribute 'display'

The ifelse function handles conditional transformations. It is similar to python’s if…else statements or SQL’s case_when function.

BREAKDOWN OF SOLUTION

• Step 1 : Define the condition, with the True and False values.

condition = f.c >= 0  # positive values
true = f.a - f.b
false = f.b - f.a

• Step 2 : Create the ifelse expression.

if_statement = ifelse(condition, true, false)

• Step 3: Apply the if_statement to the datatable frame to get the results

df[:, update(b=if_statement)]
df

	a	b	c
	▪▪▪▪	▪▪▪▪	▪▪▪▪
0	1	−1	3
1	1	1	−3
2	2	−1	2
3	4	−2	−1

4 rows × 3 columns

Transformation based on Multiple Conditions

Source data

df = dt.Frame({"Type": ["A", "B", "B", "C"], "Set": ["Z", "Z", "X", "Y"]})

df

	Type	Set
	▪▪▪▪	▪▪▪▪
0	A	Z
1	B	Z
2	B	X
3	C	Y

4 rows × 2 columns

• Task:

1. if Set is equal to ‘Z’ and Type is equal to ‘A’ then assign ‘yellow’ to color.

2. If Set is equal to ‘Z’ and Type is equal to ‘B’ then assign ‘blue’ to color.

3. If Type is equal to ‘B’ then assign ‘purple’ to color.

4. Otherwise, assign ‘black’ to color.

BREAKDOWN OF SOLUTION

• Step 1 : Define the conditions, with the True and False values.

condition1 = (f.Set == "Z") & (f.Type == "A")
true1 = "yellow"
condition2 = (f.Set == "Z") & (f.Type == "B")
true2 = "blue"
condition3 = f.Type == "B"
true3 = "purple"
false = "black"

• Step 2 : Create the ifelse expression.

if_statements = ifelse(condition1, true1, condition2, true2, condition3, true3, false)

• Step 3: Apply the if_statements to the datatable frame to get the results

df[:, update(color=if_statements)]
df

	Type	Set	color
	▪▪▪▪	▪▪▪▪	▪▪▪▪
0	A	Z	yellow
1	B	Z	blue
2	B	X	purple
3	C	Y	black

4 rows × 3 columns

Resources:

• ifelse

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