python pandas matplotlib bar-chart gantt-chart

How to plot a Gantt chart from multiple dataframe columns

I have a CSV file Master File which contains details of all the products in our repository alongwith their respective timing details (Time_In & Time_Out). I have read the CSV file into dataframe using pandas.

Can someone please tell me how can I plot the details of all the products (Product_A1,...,Product_A7) against their respective Time_In & Time_out details in a single plot using python.

What I need is something like this.

`master_df.csv`

Date_A1,Product_A1,TIme_In_A1,TIme_out_A1,Date_A2,Product_A2,TIme_In_A2,TIme_out_A2,Date_A3,Product_A3,TIme_In_A3,TIme_out_A3,Date_A4,Product_A4,TIme_In_A4,TIme_out_A4,Date_A5,Product_A5,TIme_In_A5,TIme_out_A5,Date_A6,Product_A6,TIme_In_A6,TIme_out_A6,Date_A7,Product_A7,TIme_In_A7,TIme_out_A7
07-06-2023,A1,00:00:00,00:45:00,07-06-2023,A2,00:00:00,01:03:00,07-06-2023,A3,00:00:00,00:30:00,07-06-2023,A4,00:00:00,00:15:00,07-06-2023,A5,00:00:00,00:33:00,07-06-2023,A6,00:00:00,00:48:00,07-06-2023,A7,04:00:00,05:03:00
07-06-2023,A1,00:48:00,01:00:00,07-06-2023,A2,01:06:00,01:18:00,07-06-2023,A3,00:33:00,03:33:00,07-06-2023,A4,00:18:00,02:15:00,07-06-2023,A5,00:36:00,02:18:00,07-06-2023,A6,00:51:00,01:06:00,07-06-2023,A7,05:06:00,06:21:00
07-06-2023,A1,01:03:00,01:15:00,07-06-2023,A2,01:21:00,02:45:00,07-06-2023,A3,03:36:00,04:30:00,07-06-2023,A4,02:18:00,03:18:00,07-06-2023,A5,02:21:00,03:36:00,07-06-2023,A6,01:09:00,01:21:00,07-06-2023,A7,06:24:00,07:03:00
07-06-2023,A1,01:18:00,01:30:00,07-06-2023,A2,02:48:00,03:00:00,07-06-2023,A3,04:33:00,05:30:00,07-06-2023,A4,03:21:00,04:18:00,07-06-2023,A5,03:39:00,05:48:00,07-06-2023,A6,01:24:00,01:33:00,07-06-2023,A7,07:06:00,09:09:00
07-06-2023,A1,01:33:00,01:45:00,07-06-2023,A2,03:03:00,03:15:00,07-06-2023,A3,05:33:00,06:15:00,07-06-2023,A4,04:21:00,04:33:00,07-06-2023,A5,05:51:00,06:03:00,07-06-2023,A6,01:36:00,02:48:00,07-06-2023,A7,09:12:00,10:00:00
07-06-2023,A1,01:48:00,03:30:00,07-06-2023,A2,03:18:00,03:48:00,07-06-2023,A3,06:18:00,07:18:00,07-06-2023,A4,04:36:00,04:45:00,07-06-2023,A5,06:06:00,06:48:00,07-06-2023,A6,02:51:00,03:03:00,07-06-2023,A7,10:03:00,12:30:00
07-06-2023,A1,03:33:00,03:45:00,07-06-2023,A2,03:51:00,04:00:00,07-06-2023,A3,07:21:00,08:45:00,07-06-2023,A4,04:48:00,05:33:00,07-06-2023,A5,06:51:00,07:00:00,07-06-2023,A6,03:06:00,03:21:00,07-06-2023,A7,12:33:00,12:48:00
07-06-2023,A1,03:48:00,04:00:00,07-06-2023,A2,04:03:00,04:15:00,07-06-2023,A3,08:48:00,09:03:00,07-06-2023,A4,05:36:00,05:45:00,07-06-2023,A5,07:03:00,07:30:00,07-06-2023,A6,03:24:00,05:00:00,07-06-2023,A7,12:51:00,14:00:00
07-06-2023,A1,08:00:00,09:00:00,07-06-2023,A2,04:18:00,05:15:00,07-06-2023,A3,09:06:00,11:45:00,07-06-2023,A4,05:48:00,06:18:00,07-06-2023,A5,07:33:00,08:51:00,07-06-2023,A6,05:03:00,07:21:00,07-06-2023,A7,14:03:00,14:48:00
07-06-2023,A1,09:03:00,10:15:00,07-06-2023,A2,05:18:00,06:00:00,07-06-2023,A3,11:48:00,12:00:00,07-06-2023,A4,06:21:00,06:45:00,07-06-2023,A5,08:54:00,09:06:00,07-06-2023,A6,07:24:00,07:33:00,07-06-2023,A7,14:51:00,16:18:00
07-06-2023,A1,10:18:00,10:45:00,07-06-2023,A2,06:03:00,06:30:00,07-06-2023,A3,16:00:00,16:15:00,07-06-2023,A4,06:48:00,08:48:00,07-06-2023,A5,09:09:00,09:30:00,07-06-2023,A6,07:36:00,08:30:00,07-06-2023,A7,16:21:00,17:03:00
07-06-2023,A1,10:48:00,11:15:00,07-06-2023,A2,06:33:00,07:15:00,07-06-2023,A3,16:18:00,16:30:00,07-06-2023,A4,08:51:00,10:18:00,07-06-2023,A5,09:33:00,11:33:00,07-06-2023,A6,08:33:00,10:21:00,07-06-2023,A7,17:06:00,19:15:00
07-06-2023,A1,11:18:00,11:30:00,07-06-2023,A2,07:18:00,08:00:00,07-06-2023,A3,16:33:00,17:45:00,07-06-2023,A4,10:21:00,10:30:00,07-06-2023,A5,11:36:00,12:03:00,07-06-2023,A6,10:24:00,13:21:00,07-06-2023,A7,19:18:00,19:33:00
07-06-2023,A1,11:33:00,14:15:00,07-06-2023,A2,12:00:00,13:00:00,07-06-2023,A3,17:48:00,18:45:00,07-06-2023,A4,10:33:00,11:18:00,07-06-2023,A5,12:06:00,12:15:00,07-06-2023,A6,13:24:00,14:39:00,07-06-2023,A7,19:36:00,21:48:00
07-06-2023,A1,14:18:00,14:30:00,07-06-2023,A2,13:03:00,13:30:00,07-06-2023,A3,18:48:00,19:00:00,07-06-2023,A4,11:21:00,11:48:00,07-06-2023,A5,12:18:00,12:45:00,07-06-2023,A6,14:42:00,14:45:00,07-06-2023,A7,21:51:00,22:03:00
07-06-2023,A1,14:33:00,15:15:00,07-06-2023,A2,13:33:00,13:45:00,07-06-2023,A3,19:03:00,22:15:00,07-06-2023,A4,11:51:00,12:00:00,07-06-2023,A5,12:48:00,13:18:00,07-06-2023,A6,14:48:00,16:00:00,07-06-2023,A7,22:06:00,22:33:00
07-06-2023,A1,15:18:00,16:45:00,07-06-2023,A2,13:48:00,16:48:00,07-06-2023,A3,22:30:00,01:00:00,07-06-2023,A4,12:03:00,13:15:00,07-06-2023,A5,13:21:00,13:36:00,07-06-2023,A6,16:03:00,17:00:00,07-06-2023,A7,22:36:00,23:03:00
07-06-2023,A1,16:48:00,17:30:00,07-06-2023,A2,16:51:00,19:45:00,,,,,07-06-2023,A4,13:18:00,13:33:00,07-06-2023,A5,13:39:00,14:36:00,07-06-2023,A6,17:03:00,17:15:00,07-06-2023,A7,23:06:00,23:15:00
07-06-2023,A1,17:33:00,18:30:00,07-06-2023,A2,19:48:00,20:00:00,,,,,07-06-2023,A4,13:36:00,14:33:00,07-06-2023,A5,14:39:00,16:51:00,07-06-2023,A6,17:18:00,21:33:00,07-06-2023,A7,23:18:00,01:57:00
07-06-2023,A1,18:33:00,20:30:00,07-06-2023,A2,20:03:00,20:15:00,,,,,07-06-2023,A4,14:36:00,15:00:00,07-06-2023,A5,16:54:00,17:33:00,07-06-2023,A6,21:36:00,23:33:00,,,,
07-06-2023,A1,20:33:00,21:30:00,07-06-2023,A2,20:18:00,20:33:00,,,,,07-06-2023,A4,15:03:00,16:00:00,07-06-2023,A5,17:36:00,19:30:00,07-06-2023,A6,23:36:00,00:00:00,,,,
07-06-2023,A1,21:33:00,21:45:00,07-06-2023,A2,20:36:00,20:45:00,,,,,07-06-2023,A4,20:00:00,20:48:00,07-06-2023,A5,19:33:00,19:48:00,,,,,,,,
07-06-2023,A1,21:48:00,22:15:00,07-06-2023,A2,20:48:00,21:15:00,,,,,07-06-2023,A4,20:51:00,22:00:00,07-06-2023,A5,19:51:00,20:00:00,,,,,,,,
07-06-2023,A1,22:18:00,22:30:00,07-06-2023,A2,21:18:00,22:18:00,,,,,07-06-2023,A4,22:03:00,00:48:00,,,,,,,,,,,,
07-06-2023,A1,22:33:00,23:45:00,07-06-2023,A2,22:21:00,22:45:00,,,,,,,,,,,,,,,,,,,,
07-06-2023,A1,23:48:00,00:15:00,07-06-2023,A2,22:48:00,23:00:00,,,,,,,,,,,,,,,,,,,,
,,,,07-06-2023,A2,23:03:00,23:30:00,,,,,,,,,,,,,,,,,,,,
,,,,07-06-2023,A2,23:33:00,23:48:00,,,,,,,,,,,,,,,,,,,,
,,,,07-06-2023,A2,23:51:00,01:48:00,,,,,,,,,,,,,,,,,,,,

Solution

This option plots a long dataframe with .barh, as shown in this answer.
Where 'TIme_out' is detected to be on the following day, based on the time component being smaller than for TIme_In', 1 day is added to the date, so the visualization ends at the correct time for each 'Product'.
Tested in python 3.11.3, pandas 2.0.2, matplotlib 3.7.1, numpy 1.24.3

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import numpy as np

# load the data
df = pd.read_csv('d:/data/2023-06-07_data_so.csv')

# convert the columns to datetime
for date, time_in, time_out in zip(df.columns[0::4], df.columns[2::4], df.columns[3::4]):
    df[time_in] = pd.to_datetime(df[date] + ' ' + df[time_in])
    df[time_out] = pd.to_datetime(df[date] + ' ' + df[time_out])    
    
    # if time out is less than time in, add 1 day to time out
    df[time_out] = np.where(df[time_out].lt(df[time_in]), df[time_out].add(pd.Timedelta(1, unit='D')), df[time_out])

# add an id column for use in wide_to_long
df['id'] = df.index

# convert the dataframe to long format
dfl = pd.wide_to_long(df.filter(regex='id|TIme'), stubnames=['TIme_In', 'TIme_out'], j='Product', sep='_', i='id', suffix='.+').reset_index(level=1).dropna()

# calculate the time difference
dfl['Width'] = dfl.TIme_out.sub(dfl.TIme_In)

# map Product to a color
cm = dict(zip(dfl.Product.unique(), ['#ff0000', '#92d050', '#00b0f0', '#ffff00', '#c55a11', '#7030a0', '#00b050']))
dfl['color'] = dfl.Product.map(cm)

# create fig and ax
fig, ax = plt.subplots(figsize=(15, 7), dpi=200, tight_layout=True)

# plot 
ax.barh(y='Product', width='Width', left='TIme_In', color='color', data=dfl, ec='k')

# set the x-axis limits
ax.set_xlim(dfl.TIme_In.min(), dfl.TIme_out.max())

# format the xticks and the interval
ax.xaxis.set_major_locator(mdates.MinuteLocator(byminute=range(0, 60, 30)))
ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))
fig.autofmt_xdate(rotation=90, ha="center")

`dfl.head()`

   Product             TIme_In            TIme_out           Width    color
id                                                                         
0       A1 2023-07-06 00:00:00 2023-07-06 00:45:00 0 days 00:45:00  #ff0000
1       A1 2023-07-06 00:48:00 2023-07-06 01:00:00 0 days 00:12:00  #ff0000
2       A1 2023-07-06 01:03:00 2023-07-06 01:15:00 0 days 00:12:00  #ff0000
3       A1 2023-07-06 01:18:00 2023-07-06 01:30:00 0 days 00:12:00  #ff0000
4       A1 2023-07-06 01:33:00 2023-07-06 01:45:00 0 days 00:12:00  #ff0000