Lære Diversity Metrics and Analysis | Analyzing Workforce Trends

Stryg for at vise menuen

Understanding diversity within an organization is crucial for building a healthy, innovative, and equitable workplace. Diversity metrics help you quantify the representation of different groups—such as gender, age, and ethnicity—across your workforce. By analyzing these metrics, you can identify imbalances, track progress over time, and inform strategies to foster inclusion. In people analytics, you often focus on metrics like the gender ratio, age distribution, and the proportions of various ethnic groups within your organization.


              12345678910111213141516171819
            
import pandas as pd

# Create a DataFrame with employee demographic data
data = {
    "EmployeeID": [1, 2, 3, 4, 5, 6, 7, 8],
    "Gender": ["Female", "Male", "Female", "Female", "Male", "Male", "Female", "Male"],
    "Age": [29, 34, 41, 28, 36, 30, 27, 45],
    "Ethnicity": ["Hispanic", "White", "Black", "Asian", "White", "Black", "Asian", "Hispanic"]
}
df = pd.DataFrame(data)

# Calculate gender ratio (number of females to males)
num_females = (df["Gender"] == "Female").sum()
num_males = (df["Gender"] == "Male").sum()
gender_ratio = num_females / num_males

print("Number of females:", num_females)
print("Number of males:", num_males)
print("Gender ratio (females to males):", round(gender_ratio, 2))

When you interpret diversity ratios, such as the gender ratio, you are looking at the balance between different groups. A gender ratio close to 1:1 suggests equal representation of women and men, which can contribute to a more balanced organizational culture. Imbalances in these metrics may indicate potential issues with recruitment, retention, or advancement practices. Tracking these numbers over time helps you assess the effectiveness of diversity initiatives and their impact on the workplace environment.


              1234
            
# Summarize ethnicity distribution using value_counts
ethnicity_counts = df["Ethnicity"].value_counts()
print("Ethnicity distribution:")
print(ethnicity_counts)

1. What does a gender ratio of 1:1 indicate?

2. Fill in the blank: To count unique values in a DataFrame column, use the ____ method.

3. Why is tracking diversity important for organizations?

Var alt klart?

Tak for dine kommentarer!

Sektion 2. Kapitel 1

Spørg AI

Spørg om hvad som helst eller prøv et af de foreslåede spørgsmål for at starte vores chat

Sektion 2. Kapitel 1