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Thiagobc23/gantt.py

Last active March 30, 2024 16:54
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Gantt Chart with Matplotlib v2
Raw
gantt.py
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Patch
from pandas import Timestamp
##### DATA #####
data = {'Task': {0: 'TSK M',
1: 'TSK N',
2: 'TSK L',
3: 'TSK K',
4: 'TSK J',
5: 'TSK H',
6: 'TSK I',
7: 'TSK G',
8: 'TSK F',
9: 'TSK E',
10: 'TSK D',
11: 'TSK C',
12: 'TSK B',
13: 'TSK A'},
'Department': {0: 'IT',
1: 'MKT',
2: 'ENG',
3: 'PROD',
4: 'PROD',
5: 'FIN',
6: 'MKT',
7: 'FIN',
8: 'MKT',
9: 'ENG',
10: 'FIN',
11: 'IT',
12: 'MKT',
13: 'MKT'},
'Start': {0: Timestamp('2022-03-17 00:00:00'),
1: Timestamp('2022-03-17 00:00:00'),
2: Timestamp('2022-03-10 00:00:00'),
3: Timestamp('2022-03-09 00:00:00'),
4: Timestamp('2022-03-04 00:00:00'),
5: Timestamp('2022-02-28 00:00:00'),
6: Timestamp('2022-02-28 00:00:00'),
7: Timestamp('2022-02-27 00:00:00'),
8: Timestamp('2022-02-26 00:00:00'),
9: Timestamp('2022-02-23 00:00:00'),
10: Timestamp('2022-02-22 00:00:00'),
11: Timestamp('2022-02-21 00:00:00'),
12: Timestamp('2022-02-19 00:00:00'),
13: Timestamp('2022-02-15 00:00:00')},
'End': {0: Timestamp('2022-03-20 00:00:00'),
1: Timestamp('2022-03-19 00:00:00'),
2: Timestamp('2022-03-13 00:00:00'),
3: Timestamp('2022-03-13 00:00:00'),
4: Timestamp('2022-03-17 00:00:00'),
5: Timestamp('2022-03-02 00:00:00'),
6: Timestamp('2022-03-05 00:00:00'),
7: Timestamp('2022-03-03 00:00:00'),
8: Timestamp('2022-02-27 00:00:00'),
9: Timestamp('2022-03-09 00:00:00'),
10: Timestamp('2022-03-01 00:00:00'),
11: Timestamp('2022-03-03 00:00:00'),
12: Timestamp('2022-02-24 00:00:00'),
13: Timestamp('2022-02-20 00:00:00')},
'Completion': {0: 0.0,
1: 0.0,
2: 0.0,
3: 0.0,
4: 0.0,
5: 1.0,
6: 0.4,
7: 0.7,
8: 1.0,
9: 0.5,
10: 1.0,
11: 0.9,
12: 1.0,
13: 1.0}}
##### DATA PREP #####
df = pd.DataFrame(data)
# project start date
proj_start = df.Start.min()
# number of days from project start to task start
df['start_num'] = (df.Start-proj_start).dt.days
# number of days from project start to end of tasks
df['end_num'] = (df.End-proj_start).dt.days
# days between start and end of each task
df['days_start_to_end'] = df.end_num - df.start_num
# days between start and current progression of each task
df['current_num'] = (df.days_start_to_end * df.Completion)
# create a column with the color for each department
def color(row):
c_dict = {'MKT':'#E64646', 'FIN':'#E69646', 'ENG':'#34D05C', 'PROD':'#34D0C3', 'IT':'#3475D0'}
return c_dict[row['Department']]
df['color'] = df.apply(color, axis=1)
##### PLOT #####
fig, (ax, ax1) = plt.subplots(2, figsize=(16,6), gridspec_kw={'height_ratios':[6, 1]}, facecolor='#36454F')
ax.set_facecolor('#36454F')
ax1.set_facecolor('#36454F')
# bars
ax.barh(df.Task, df.current_num, left=df.start_num, color=df.color)
ax.barh(df.Task, df.days_start_to_end, left=df.start_num, color=df.color, alpha=0.5)
for idx, row in df.iterrows():
ax.text(row.end_num+0.1, idx, f"{int(row.Completion*100)}%", va='center', alpha=0.8, color='w')
ax.text(row.start_num-0.1, idx, row.Task, va='center', ha='right', alpha=0.8, color='w')
# grid lines
ax.set_axisbelow(True)
ax.xaxis.grid(color='k', linestyle='dashed', alpha=0.4, which='both')
# ticks
xticks = np.arange(0, df.end_num.max()+1, 3)
xticks_labels = pd.date_range(proj_start, end=df.End.max()).strftime("%m/%d")
xticks_minor = np.arange(0, df.end_num.max()+1, 1)
ax.set_xticks(xticks)
ax.set_xticks(xticks_minor, minor=True)
ax.set_xticklabels(xticks_labels[::3], color='w')
ax.set_yticks([])
plt.setp([ax.get_xticklines()], color='w')
# align x axis
ax.set_xlim(0, df.end_num.max())
# remove spines
ax.spines['right'].set_visible(False)
ax.spines['left'].set_visible(False)
ax.spines['left'].set_position(('outward', 10))
ax.spines['top'].set_visible(False)
ax.spines['bottom'].set_color('w')
plt.suptitle('PROJECT XYZ', color='w')
##### LEGENDS #####
legend_elements = [Patch(facecolor='#E64646', label='Marketing'),
Patch(facecolor='#E69646', label='Finance'),
Patch(facecolor='#34D05C', label='Engineering'),
Patch(facecolor='#34D0C3', label='Production'),
Patch(facecolor='#3475D0', label='IT')]
legend = ax1.legend(handles=legend_elements, loc='upper center', ncol=5, frameon=False)
plt.setp(legend.get_texts(), color='w')
# clean second axis
ax1.spines['right'].set_visible(False)
ax1.spines['left'].set_visible(False)
ax1.spines['top'].set_visible(False)
ax1.spines['bottom'].set_visible(False)
ax1.set_xticks([])
ax1.set_yticks([])
plt.savefig('gantt.png', facecolor='#36454F')
Raw
gantt_withTodayMark.py
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Patch
from pandas import Timestamp
##### DATA #####
data = {'Task': {0: 'TSK M',
1: 'TSK N',
2: 'TSK L',
3: 'TSK K',
4: 'TSK J',
5: 'TSK H',
6: 'TSK I',
7: 'TSK G',
8: 'TSK F',
9: 'TSK E',
10: 'TSK D',
11: 'TSK C',
12: 'TSK B',
13: 'TSK A'},
'Department': {0: 'IT',
1: 'MKT',
2: 'ENG',
3: 'PROD',
4: 'PROD',
5: 'FIN',
6: 'MKT',
7: 'FIN',
8: 'MKT',
9: 'ENG',
10: 'FIN',
11: 'IT',
12: 'MKT',
13: 'MKT'},
'Start': {0: Timestamp('2022-03-17 00:00:00'),
1: Timestamp('2022-03-17 00:00:00'),
2: Timestamp('2022-03-10 00:00:00'),
3: Timestamp('2022-03-09 00:00:00'),
4: Timestamp('2022-03-04 00:00:00'),
5: Timestamp('2022-02-28 00:00:00'),
6: Timestamp('2022-02-28 00:00:00'),
7: Timestamp('2022-02-27 00:00:00'),
8: Timestamp('2022-02-26 00:00:00'),
9: Timestamp('2022-02-23 00:00:00'),
10: Timestamp('2022-02-22 00:00:00'),
11: Timestamp('2022-02-21 00:00:00'),
12: Timestamp('2022-02-19 00:00:00'),
13: Timestamp('2022-02-15 00:00:00')},
'End': {0: Timestamp('2022-03-20 00:00:00'),
1: Timestamp('2022-03-19 00:00:00'),
2: Timestamp('2022-03-13 00:00:00'),
3: Timestamp('2022-03-13 00:00:00'),
4: Timestamp('2022-03-17 00:00:00'),
5: Timestamp('2022-03-02 00:00:00'),
6: Timestamp('2022-03-05 00:00:00'),
7: Timestamp('2022-03-03 00:00:00'),
8: Timestamp('2022-02-27 00:00:00'),
9: Timestamp('2022-03-09 00:00:00'),
10: Timestamp('2022-03-01 00:00:00'),
11: Timestamp('2022-03-03 00:00:00'),
12: Timestamp('2022-02-24 00:00:00'),
13: Timestamp('2022-02-20 00:00:00')},
'Completion': {0: 0.0,
1: 0.0,
2: 0.0,
3: 0.0,
4: 0.0,
5: 1.0,
6: 0.4,
7: 0.7,
8: 1.0,
9: 0.5,
10: 1.0,
11: 0.9,
12: 1.0,
13: 1.0}}
##### DATA PREP #####
df = pd.DataFrame(data)
# project start date
proj_start = df.Start.min()
# number of days from project start to task start
df['start_num'] = (df.Start-proj_start).dt.days
# number of days from project start to end of tasks
df['end_num'] = (df.End-proj_start).dt.days
# days between start and end of each task
df['days_start_to_end'] = df.end_num - df.start_num
# days between start and current progression of each task
df['current_num'] = (df.days_start_to_end * df.Completion)
# create a column with the color for each department
def color(row):
c_dict = {'MKT':'#E64646', 'FIN':'#E69646', 'ENG':'#34D05C', 'PROD':'#34D0C3', 'IT':'#3475D0'}
return c_dict[row['Department']]
df['color'] = df.apply(color, axis=1)
##### PLOT #####
fig, (ax, ax1) = plt.subplots(2, figsize=(16,6), gridspec_kw={'height_ratios':[6, 1]}, facecolor='#36454F')
ax.set_facecolor('#36454F')
ax1.set_facecolor('#36454F')
# bars
ax.barh(df.Task, df.current_num, left=df.start_num, color=df.color)
ax.barh(df.Task, df.days_start_to_end, left=df.start_num, color=df.color, alpha=0.5)
for idx, row in df.iterrows():
ax.text(row.end_num+0.1, idx, f"{int(row.Completion*100)}%", va='center', alpha=0.8, color='w')
ax.text(row.start_num-0.1, idx, row.Task, va='center', ha='right', alpha=0.8, color='w')
# grid lines
ax.set_axisbelow(True)
ax.xaxis.grid(color='k', linestyle='dashed', alpha=0.4, which='both')
# ticks
xticks = np.arange(0, df.end_num.max()+1, 3)
xticks_labels = pd.date_range(proj_start, end=df.End.max()).strftime("%m/%d")
xticks_minor = np.arange(0, df.end_num.max()+1, 1)
ax.set_xticks(xticks)
ax.set_xticks(xticks_minor, minor=True)
ax.set_xticklabels(xticks_labels[::3], color='w')
ax.set_yticks([])
plt.setp([ax.get_xticklines()], color='w')
# align x axis
ax.set_xlim(0, df.end_num.max())
# remove spines
ax.spines['right'].set_visible(False)
ax.spines['left'].set_visible(False)
ax.spines['left'].set_position(('outward', 10))
ax.spines['top'].set_visible(False)
ax.spines['bottom'].set_color('w')
plt.suptitle('PROJECT XYZ', color='w')
##### LEGENDS #####
legend_elements = [Patch(facecolor='#E64646', label='Marketing'),
Patch(facecolor='#E69646', label='Finance'),
Patch(facecolor='#34D05C', label='Engineering'),
Patch(facecolor='#34D0C3', label='Production'),
Patch(facecolor='#3475D0', label='IT')]
legend = ax1.legend(handles=legend_elements, loc='upper center', ncol=5, frameon=False)
plt.setp(legend.get_texts(), color='w')
# clean second axis
ax1.spines['right'].set_visible(False)
ax1.spines['left'].set_visible(False)
ax1.spines['top'].set_visible(False)
ax1.spines['bottom'].set_visible(False)
ax1.set_xticks([])
ax1.set_yticks([])
# Get "Today" value from sys date/ date.today()
#from datetime import date
#today = pd.Timestamp(date.today())
#today = today - proj_start
# Get "Today" value from custom timestamp
today = Timestamp('2022-03-02 00:00:00')
today = today - proj_start
# plot line for today
ax.axvline(today.days, color='w', lw=1, alpha=0.7)
ax.text(today.days, len(df)+0.5, 'Today', ha='center', color='w')
plt.savefig('gantt.png', facecolor='#36454F')
@divuShankar
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This code is very insightful! I am trying to implement something similar, but would like the x-axis to be in Months. For instance instead of displaying Week 1, Week 2, Week 3, etc.. I would like to have January, February, March, etc.. Could you help me with this?

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