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import streamlit as st | |
import pandas as pd | |
import matplotlib.pyplot as plt | |
def process_data(df): | |
# Convert dates and filter relevant period | |
df['Start Date'] = pd.to_datetime(df['Date'].str.split(' to ').str[0], format='%d/%b/%y') | |
df['End Date'] = pd.to_datetime(df['Date'].str.split(' to ').str[1], format='%d/%b/%y') | |
# Categorize into weeks | |
df['Week'] = df['Start Date'].apply(lambda x: 1 if x <= pd.Timestamp('2025-01-05') else 2) | |
return df | |
def create_utilization_chart(week_data, week_number): | |
fig, ax = plt.subplots() | |
wedges, texts, autotexts = ax.pie( | |
week_data[['Billable', 'Non-Billable', 'Leaves']].values[0], | |
labels=['Billable', 'Non-Billable', 'Leaves'], | |
autopct='%1.1f%%', | |
colors=['#4CAF50', '#FFC107', '#9E9E9E'] | |
) | |
plt.setp(autotexts, size=10, weight="bold", color='white') | |
ax.set_title(f'Week {week_number} Utilization', pad=20) | |
return fig | |
def create_non_billable_breakdown(df): | |
non_billable = df[df['Project Category'] == 'Non-Billable'] | |
breakdown = non_billable.groupby('Epic')['Logged'].sum().reset_index() | |
breakdown = breakdown[breakdown['Epic'] != 'No Epic'] | |
fig, ax = plt.subplots() | |
breakdown.plot(kind='bar', x='Epic', y='Logged', ax=ax, legend=False) | |
ax.set_title('Non-Billable Time Breakdown') | |
ax.set_ylabel('Hours') | |
plt.xticks(rotation=45) | |
return fig | |
def main(): | |
st.title('QA Team Utilization Dashboard') | |
uploaded_file = st.file_uploader("Upload Tempo Timesheet", type=['xls', 'xlsx']) | |
if uploaded_file: | |
df = pd.read_excel(uploaded_file, sheet_name='Report') | |
df = process_data(df) | |
# Page 4 Visualization | |
st.header("Bi-Weekly Utilization Report") | |
col1, col2 = st.columns(2) | |
with col1: | |
week1 = df[df['Week'] == 1] | |
st.pyplot(create_utilization_chart(week1, 1)) | |
with col2: | |
week2 = df[df['Week'] == 2] | |
st.pyplot(create_utilization_chart(week2, 2)) | |
# Page 5 Visualization | |
st.header("Non-Billable Time Breakdown") | |
st.pyplot(create_non_billable_breakdown(df)) | |
# Page 6 Visualization | |
st.header("Solution Accelerators Progress") | |
accelerators = df[(df['Project Category'] == 'Non-Billable') & | |
(df['Epic'] == 'Solution Accelerators')] | |
st.dataframe( | |
accelerators[['Project', 'Logged', 'Key']].rename(columns={ | |
'Project': 'Initiative', | |
'Logged': 'Hours', | |
'Key': 'Status' | |
}), | |
hide_index=True | |
) | |
if __name__ == "__main__": | |
main() |