Subsetting Single-Case Experimental Design Data#
The subset_scd
function allows filtering a single-case dataset based on a specified logical condition.
Filtering Data with subset_scd
#
The subset_scd
function filters a single-case dataset by applying a logical condition.
Required Arguments:#
scdf
: A Pandas DataFrame containing SCED data.condition
: A string-based condition used for filtering (e.g.,'teacher == 1'
).
The function returns a DataFrame containing only the rows that match the given condition. If an invalid condition is provided, an error will be raised.
import scia as sc
📖 scia 1.101.0.dev6 - For Documentation, visit: https://ahsankhodami.github.io/scia/intro.html
Example 1: Filtering Data Based on a Condition#
In this example, we filter the dataset to include only rows where teacher == 1
.
import pandas as pd
# Create a sample dataset
df = pd.DataFrame({
"case": ["A", "A", "B", "B", "C", "C"],
"phase": ["Baseline", "Intervention", "Baseline", "Intervention", "Baseline", "Intervention"],
"values": [5, 6, 3, 7, 2, 8],
"teacher": [1, 0, 1, 1, 0, 0]
})
# Apply filtering
df_filtered = sc.subset_scd(df, "teacher == 1")
print(df_filtered)
case phase values teacher
0 A Baseline 5 1
2 B Baseline 3 1
3 B Intervention 7 1
Example 2: Filtering Data Using Multiple Conditions#
Filtering the dataset to include only rows where teacher == 1
and values > 4
.
df_filtered = sc.subset_scd(df, "teacher == 1 and values > 4")
print(df_filtered)
case phase values teacher
0 A Baseline 5 1
3 B Intervention 7 1