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"""
A file that will visualize salary data from an incoming CSV.
This script reads a CSV file containing salary data and visualizes it using
plotly.
"""
import locale
from pandas import read_csv as pd_read_csv
import pandas as pd
import plotly.graph_objs as go
locale.setlocale(locale.LC_ALL, 'en_US.UTF-8')
# Read the CSV file
df = pd_read_csv('~/git/cmc.pub/theme/static/salary.csv')
def format_currency(value: float) -> str:
"""
Format values in USD currency format.
Args:
value (float): The value to be formatted.
Returns:
str: The formatted value.
"""
return f"${value:,.2f}"
# Reverse the order of the DataFrame
df = df.iloc[::-1].reset_index(drop=True)
# Calculate the percentage increase
df['Percentage Increase'] = df['Salary'].pct_change() * 100
def create_trace(row: pd.Series) -> go.Scatter:
"""
Create a scatter plot trace for a single row.
Args:
row (pd.Series): The row to be plotted.
Returns:
go.Scatter: The created scatter plot trace.
"""
title_company = f"{row['Title']} ({row['Company']})"
salary_formatted = format_currency(row['Salary'])
if pd.notna(row['Percentage Increase']):
text = f"{salary_formatted} ({row['Percentage Increase']:.2f}%)"
else:
text = salary_formatted
return go.Scatter(
x=[row['Start'], row['End']],
y=[row['Salary'], row['Salary']],
text=[text],
mode='lines+text',
name=title_company,
textposition='top center'
)
# Initialize the plot
fig = go.Figure()
# Add each data point as a separate trace to display the text
for index, df_row in df.iterrows():
fig.add_trace(create_trace(df_row))
# Update visual styles of the figure
fig.update_layout(
title="Salary Data Over Time (annualized)",
xaxis_title="Time",
yaxis_title="Salary",
font={"family": 'monospace', "size": 16},
margin={"l": 50, "r": 50, "t": 50, "b": 100},
legend={
"orientation": 'h',
"yanchor": 'top',
"y": -0.3,
"xanchor": 'center',
"x": 0.5
},
height=800
)
# Display the plot
fig.show()
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