Row
Chart A
'data.frame': 492 obs. of 5 variables:
$ Month : chr "August" "July" "June" "May" ...
$ Year : int 2023 2023 2023 2023 2023 2023 2023 2023 2022 2022 ...
$ PRODUCTS : chr "ATF" "ATF" "ATF" "ATF" ...
$ Quantity..000.Metric.Tonnes.: num 677 663 642 671 656 ...
$ updated_date : chr "2024-01-03" "2024-01-03" "2024-01-03" "2024-01-03" ... Month Year PRODUCTS
Length:492 Min. :2020 Length:492
Class :character 1st Qu.:2021 Class :character
Mode :character Median :2021 Mode :character
Mean :2021
3rd Qu.:2022
Max. :2023
Quantity..000.Metric.Tonnes. updated_date
Min. : 23.24 Length:492
1st Qu.: 362.07 Class :character
Median : 858.27 Mode :character
Mean :1453.35
3rd Qu.:1967.88
Max. :8217.12 Chart B
[1] 0
Row
Chart C
Chart D
Row
Chart E
Chart F
# A tibble: 12 × 6
PRODUCTS Mean_Quantity Median_Quantity Std_Dev_Quantity Min_Quantity
<chr> <dbl> <dbl> <dbl> <dbl>
1 ATF 473. 479. 166. 55
2 Bitumen 656. 708. 219. 187
3 FO & LSHS 526. 529 64.1 283
4 HSD 6653. 6676. 968. 3252
5 LDO 71.5 69 15.6 28
6 LPG 2339. 2356. 132. 2064
7 Lubricants & Gre… 342. 333. 74.2 148
8 MS 2665. 2740 412. 973
9 Naphtha 1099. 1113. 135. 730
10 Others 1143. 1116. 322. 680
11 Petroleum coke 1376. 1382. 360. 775
12 SKO 97.7 119. 50.1 23.2
# ℹ 1 more variable: Max_Quantity <dbl>