[Term Entry] Python - Pandas groupBy: size()

content/pandas/concepts/groupby/terms/size/size.md

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+---
+Title: 'size()'
+Description: 'Returns a Series containing the size (row count) of each group.'
+Subjects:
+  - 'Computer Science'
+  - 'Data Science'
+Tags:
+  - 'Data Structures'
+  - 'Pandas'
+CatalogContent:
+  - 'learn-python-3'
+  - 'paths/data-science'
+---
+
+The **`groupby().size()`** method in pandas returns the number of rows or elements in each group created by the `groupby()` function. It provides a quick way to determine group sizes without applying an aggregation function.
+
+## Syntax
+
+```pseudo
+DataFrameGroupBy.size()
+```
+
+**Parameters:**
+
+The `size()` method does not take any parameters.
+
+**Return value:**
+
+The `size()` method returns a Series containing the size (row count) of each group created by `groupby()`.
+
+## Example 1: Counting rows by group
+
+In this example, a DataFrame of employees is grouped by their department, and `size()` counts how many employees belong to each department:
+
+```py
+import pandas as pd
+
+data = {
+    'Department': ['HR', 'IT', 'HR', 'Finance', 'IT', 'Finance'],
+    'Employee': ['John', 'Sara', 'Mike', 'Anna', 'Tom', 'Chris']
+}
+df = pd.DataFrame(data)
+
+group_sizes = df.groupby('Department').size()
+print(group_sizes)
+```
+
+The output of this code is:
+
+```shell
+Department
+Finance    2
+HR         2
+IT         2
+dtype: int64
+```
+
+## Example 2: Using multiple grouping columns
+
+In this example, `size()` counts the number of members in each combination of team and shift within a dataset:
+
+```py
+import pandas as pd
+
+data = {
+    'Team': ['A', 'A', 'B', 'B', 'B', 'C'],
+    'Shift': ['Day', 'Night', 'Day', 'Night', 'Day', 'Day'],
+    'Name': ['John', 'Sara', 'Mike', 'Anna', 'Tom', 'Chris']
+}
+df = pd.DataFrame(data)
+
+group_sizes = df.groupby(['Team', 'Shift']).size()
+print(group_sizes)
+```
+
+The output of this code is:
+
+```shell
+Team  Shift
+A     Day      1
+      Night    1
+B     Day      2
+      Night    1
+C     Day      1
+dtype: int64
+```
+
+## Codebyte Example: Counting transactions per product
+
+In this example, `size()` is used to count how many sales transactions occurred for each product in a store dataset:
+
+```codebyte/python
+import pandas as pd
+
+sales = pd.DataFrame({
+  'Product': ['Apple', 'Banana', 'Apple', 'Orange', 'Banana', 'Banana', 'Apple'],
+  'Customer': ['A', 'B', 'C', 'A', 'D', 'E', 'F']
+})
+
+counts = sales.groupby('Product').size()
+print(counts)
+```
+
+## Frequently Asked Questions
+
+### 1. What is the pandas groupby size method?
+
+`groupby().size()` returns the number of rows in each group created by `groupby()`.
+
+###2. What is the purpose of `groupby()` in pandas?
+
+`groupby()` splits data into groups based on selected column values to enable aggregation and summarization.
+
+### 3. What does `NaN` stand for in pandas?
+
+`NaN` stands for Not a Number and indicates missing or undefined data.