HR Productivity Correlogram

import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np

np.random.seed(222)

n = 170
dept = np.random.choice(['Engineering', 'Sales', 'Marketing'], n)
data = {
    'Productivity': np.where(dept == 'Engineering', np.random.normal(85, 10, n),
                            np.where(dept == 'Sales', np.random.normal(78, 15, n), np.random.normal(80, 12, n))),
    'Satisfaction': np.where(dept == 'Engineering', np.random.normal(72, 12, n),
                            np.where(dept == 'Sales', np.random.normal(68, 15, n), np.random.normal(75, 10, n))),
    'Tenure (yrs)': np.where(dept == 'Engineering', np.random.normal(5, 2, n),
                            np.where(dept == 'Sales', np.random.normal(3, 1.5, n), np.random.normal(4, 1.8, n))),
    'Training (hrs)': np.random.normal(40, 15, n),
    'Department': dept
}
df = pd.DataFrame(data)

sns.set_style("whitegrid", {'axes.facecolor': '#ffffff', 'figure.facecolor': '#ffffff', 'grid.color': '#eeeeee'})

palette = {'Engineering': '#27D3F5', 'Sales': '#F5276C', 'Marketing': '#F5B027'}

g = sns.pairplot(
    df,
    hue='Department',
    palette=palette,
    height=2,
    kind='scatter',
    diag_kind='kde',
    markers=['s', 'o', '^'],
    plot_kws={'alpha': 0.7, 's': 55, 'edgecolor': 'white', 'linewidths': 0.6},
    diag_kws={'alpha': 0.5, 'linewidth': 2.5, 'fill': True}
)

g.fig.set_facecolor('#ffffff')
for ax in g.axes.flat:
    if ax:
        ax.set_facecolor('#ffffff')
        for spine in ax.spines.values():
            spine.set_color('#dddddd')
        ax.tick_params(colors='#666666')
        ax.xaxis.label.set_color('#333333')
        ax.yaxis.label.set_color('#333333')

g.fig.suptitle('Workforce Analytics Dashboard', fontsize=14, fontweight='bold', color='#1a1a1a', y=1.02)

plt.tight_layout()
plt.show()