In [1]:
import pandas as pd
In [2]:
df = pd.read_csv('result.csv')
df
Out[2]:
Order_ID Product Quantity Price Total Order_Date Address Month Hour Day_name
0 176558 USB-C Charging Cable 2 11.95 23.90 2019-04-19 08:46:00 917 1st St, Dallas, TX 75001 4 8 Friday
1 176559 Bose SoundSport Headphones 1 99.99 99.99 2019-04-07 22:30:00 682 Chestnut St, Boston, MA 02215 4 22 Sunday
2 176560 Google Phone 1 600.00 600.00 2019-04-12 14:38:00 669 Spruce St, Los Angeles, CA 90001 4 14 Friday
3 176560 Wired Headphones 1 11.99 11.99 2019-04-12 14:38:00 669 Spruce St, Los Angeles, CA 90001 4 14 Friday
4 176561 Wired Headphones 1 11.99 11.99 2019-04-30 09:27:00 333 8th St, Los Angeles, CA 90001 4 9 Tuesday
... ... ... ... ... ... ... ... ... ... ...
185945 259353 AAA Batteries (4-pack) 3 2.99 8.97 2019-09-17 20:56:00 840 Highland St, Los Angeles, CA 90001 9 20 Tuesday
185946 259354 iPhone 1 700.00 700.00 2019-09-01 16:00:00 216 Dogwood St, San Francisco, CA 94016 9 16 Sunday
185947 259355 iPhone 1 700.00 700.00 2019-09-23 07:39:00 220 12th St, San Francisco, CA 94016 9 7 Monday
185948 259356 34in Ultrawide Monitor 1 379.99 379.99 2019-09-19 17:30:00 511 Forest St, San Francisco, CA 94016 9 17 Thursday
185949 259357 USB-C Charging Cable 1 11.95 11.95 2019-09-30 00:18:00 250 Meadow St, San Francisco, CA 94016 9 0 Monday

185950 rows × 10 columns

In [3]:
result = df.groupby('Day_name').agg(['sum', 'count'])['Total']
result
Out[3]:
sum count
Day_name
Friday 4.855938e+06 26247
Monday 4.883327e+06 26547
Saturday 4.904357e+06 26492
Sunday 4.932170e+06 26551
Thursday 4.839465e+06 26461
Tuesday 5.087957e+06 27175
Wednesday 4.988822e+06 26477
In [4]:
result.sort_values('sum')
Out[4]:
sum count
Day_name
Thursday 4.839465e+06 26461
Friday 4.855938e+06 26247
Monday 4.883327e+06 26547
Saturday 4.904357e+06 26492
Sunday 4.932170e+06 26551
Wednesday 4.988822e+06 26477
Tuesday 5.087957e+06 27175
In [7]:
result2 = result.sort_values('count')
result2
Out[7]:
sum count
Day_name
Friday 4.855938e+06 26247
Thursday 4.839465e+06 26461
Wednesday 4.988822e+06 26477
Saturday 4.904357e+06 26492
Monday 4.883327e+06 26547
Sunday 4.932170e+06 26551
Tuesday 5.087957e+06 27175
In [9]:
import matplotlib.pyplot as plt
In [10]:
plt.figure(figsize=(10, 6))
plt.plot(result2.index, result2['count'])
plt.gcf().axes[0].yaxis.get_major_formatter().set_scientific(False)

# plt.xticks(range(0, 24))
# plt.yticks(range(0, int(round(result['count'].max()))+5000, 1000))

plt.xlabel('Дни')
plt.ylabel('Кол-во покупок')

for index, value in enumerate(result2['count']):
    plt.text(
        index,
        value,
        value,
        rotation=90,
        size='10',
        color='#000',
        ha='center')

plt.grid()
# plt.savefig('Count.png', dpi=100)
plt.show()
In [ ]: