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import pandas as pd | |
import gspread | |
import gradio as gr | |
import plotly.express as px | |
from oauth2client.service_account import ServiceAccountCredentials | |
# ------------------ AUTH ------------------ | |
VALID_USERS = { | |
"andrew@lortechnologies.com": "Pass.123", | |
"phonnie@carfind.co.za": "Pass.123", | |
"monique@carfind.co.za": "Pass.123" | |
} | |
# ------------------ GOOGLE SHEET SETUP ------------------ | |
scope = ["https://spreadsheets.google.com/feeds", "https://www.googleapis.com/auth/drive"] | |
creds = ServiceAccountCredentials.from_json_keyfile_name("tough-star.json", scope) | |
client = gspread.authorize(creds) | |
sheet_url = "https://docs.google.com/spreadsheets/d/1bpeFS6yihb6niCavpwjWmVEypaSkGxONGg2jZfKX_sA" | |
sheet = client.open_by_url(sheet_url).worksheet("Calls") | |
data = sheet.get_all_records() | |
df = pd.DataFrame(data) | |
# ------------------ DATA CLEANING ------------------ | |
df['Timestamp'] = pd.to_datetime(df['Timestamp'], dayfirst=True, errors='coerce') | |
df['Date'] = df['Timestamp'].dt.date.astype(str) | |
df['Time'] = df['Timestamp'].dt.time | |
location_split = df['Location'].str.split(',', expand=True) | |
df['Latitude'] = pd.to_numeric(location_split[0], errors='coerce') | |
df['Longitude'] = pd.to_numeric(location_split[1], errors='coerce') | |
df = df.dropna(subset=['Date', 'Rep Name', 'Latitude', 'Longitude']) | |
df = df[(df['Latitude'] != 0) & (df['Longitude'] != 0)] | |
df = df.sort_values(by=['Rep Name', 'Timestamp']) | |
df['Time Diff (min)'] = df.groupby(['Rep Name', 'Date'])['Timestamp'].diff().dt.total_seconds().div(60).fillna(0) | |
df['Visit Order'] = df.groupby(['Rep Name', 'Date']).cumcount() + 1 | |
ALL_REPS = sorted(df['Rep Name'].dropna().unique()) | |
# ------------------ DASHBOARD FUNCTIONS ------------------ | |
def generate_summary(date_str): | |
day_df = df[df['Date'] == date_str] | |
active = day_df.groupby('Rep Name').size().reset_index(name='Total Visits') | |
active_list = active['Rep Name'].tolist() | |
inactive_list = [rep for rep in ALL_REPS if rep not in active_list] | |
inactive_df = pd.DataFrame({'Inactive Reps': inactive_list}) | |
return active, inactive_df | |
def get_reps(date_str): | |
reps = df[df['Date'] == date_str]['Rep Name'].dropna().unique() | |
return gr.update(choices=sorted(reps)) | |
def show_map(date_str, rep): | |
subset = df[(df['Date'] == date_str) & (df['Rep Name'] == rep)] | |
if subset.empty: | |
return "No valid data", None | |
subset = subset.sort_values(by='Timestamp').copy() | |
subset['Visit Order'] = range(1, len(subset) + 1) | |
center_lat = subset['Latitude'].mean() | |
center_lon = subset['Longitude'].mean() | |
fig = px.line_mapbox( | |
subset, | |
lat="Latitude", lon="Longitude", | |
hover_name="Dealership Name", | |
hover_data={"Time": True, "Time Diff (min)": True, "Visit Order": True}, | |
height=700, | |
zoom=13, | |
center={"lat": center_lat, "lon": center_lon} | |
) | |
scatter = px.scatter_mapbox( | |
subset, | |
lat="Latitude", lon="Longitude", | |
color="Visit Order", | |
hover_name="Dealership Name", | |
hover_data=["Time", "Time Diff (min)"], | |
color_continuous_scale="Bluered" | |
) | |
for trace in scatter.data: | |
fig.add_trace(trace) | |
fig.add_trace(px.scatter_mapbox( | |
pd.DataFrame([subset.iloc[0]]), | |
lat="Latitude", lon="Longitude", | |
text=["Start"], color_discrete_sequence=["green"]).data[0]) | |
fig.add_trace(px.scatter_mapbox( | |
pd.DataFrame([subset.iloc[-1]]), | |
lat="Latitude", lon="Longitude", | |
text=["End"], color_discrete_sequence=["red"]).data[0]) | |
fig.update_layout(mapbox_style="open-street-map", title=f"๐ {rep}'s Route on {date_str}") | |
table = subset[[ | |
'Visit Order', 'Dealership Name', 'Time', 'Time Diff (min)', | |
'Type of call', 'Sales or service' | |
]].rename(columns={ | |
'Dealership Name': '๐งญ Dealer', | |
'Time': '๐ Time', | |
'Time Diff (min)': 'โฑ๏ธ Time Spent', | |
'Type of call': '๐ Call Type', | |
'Sales or service': '๐ผ Category' | |
}) | |
total_time = round(table['โฑ๏ธ Time Spent'].sum(), 2) | |
summary_row = pd.DataFrame([{ | |
'Visit Order': '', | |
'๐งญ Dealer': f"๐งฎ Total Time: {total_time} min", | |
'๐ Time': '', | |
'โฑ๏ธ Time Spent': '', | |
'๐ Call Type': '', | |
'๐ผ Category': '' | |
}]) | |
table = pd.concat([table, summary_row], ignore_index=True) | |
return table, fig | |
# ------------------ GRADIO APP ------------------ | |
with gr.Blocks() as app: | |
with gr.Row(): | |
with gr.Column(visible=True) as login_ui: | |
gr.Markdown("## ๐ Login Required") | |
email = gr.Textbox(label="Email") | |
password = gr.Textbox(label="Password", type="password") | |
login_btn = gr.Button("Login") | |
login_msg = gr.Markdown("") | |
with gr.Column(visible=False) as main_ui: | |
gr.Markdown("## ๐๏ธ Carfind Rep Tracker") | |
with gr.Tab("๐ Summary"): | |
date_summary = gr.Dropdown(label="Select Date", choices=sorted(df['Date'].unique(), reverse=True)) | |
active_table = gr.Dataframe(label="โ Active Reps (with total visits)") | |
inactive_table = gr.Dataframe(label="โ ๏ธ Inactive Reps") | |
date_summary.change(fn=generate_summary, inputs=date_summary, outputs=[active_table, inactive_table]) | |
with gr.Tab("๐ค KAM's"): | |
with gr.Row(): | |
with gr.Column(scale=1): | |
date_picker = gr.Dropdown(label="Select Date", choices=sorted(df['Date'].unique(), reverse=True)) | |
rep_picker = gr.Dropdown(label="Select Rep") | |
btn = gr.Button("Show Route") | |
with gr.Column(scale=2): | |
table = gr.Dataframe(label="Call Table") | |
map_plot = gr.Plot(label="Map") | |
date_picker.change(fn=get_reps, inputs=date_picker, outputs=rep_picker) | |
btn.click(fn=show_map, inputs=[date_picker, rep_picker], outputs=[table, map_plot]) | |
def do_login(user, pw): | |
if VALID_USERS.get(user) == pw: | |
return gr.update(visible=False), gr.update(visible=True), "" | |
else: | |
return gr.update(visible=True), gr.update(visible=False), "โ Invalid email or password." | |
login_btn.click(fn=do_login, inputs=[email, password], outputs=[login_ui, main_ui, login_msg]) | |
app.launch() | |