ID int64 1 1.8k | Type stringclasses 3
values | Price int64 100 32k | Market stringclasses 1
value | Date stringdate 2024-04-01 00:00:00 2026-03-20 00:00:00 | Festival stringclasses 7
values | Season stringclasses 3
values | burmese_date stringlengths 20 29 | before_sabbath_eva bool 2
classes | after_sabbath_eva bool 2
classes |
|---|---|---|---|---|---|---|---|---|---|
1 | S | 2,000 | MALETHA | 2024-04-01 | null | Hot/Dry Season | 2567 Tabaung, Waning, 8 | false | false |
2 | N | 10,000 | MALETHA | 2024-04-01 | null | Hot/Dry Season | 2567 Tabaung, Waning, 8 | false | false |
3 | B | 8,000 | MALETHA | 2024-04-01 | null | Hot/Dry Season | 2567 Tabaung, Waning, 8 | false | false |
4 | S | 1,000 | MALETHA | 2024-04-02 | null | Hot/Dry Season | 2567 Tabaung, Waning, 9 | false | false |
5 | N | 8,000 | MALETHA | 2024-04-02 | null | Hot/Dry Season | 2567 Tabaung, Waning, 9 | false | false |
6 | B | 8,000 | MALETHA | 2024-04-02 | null | Hot/Dry Season | 2567 Tabaung, Waning, 9 | false | false |
7 | S | 500 | MALETHA | 2024-04-03 | null | Hot/Dry Season | 2567 Tabaung, Waning, 10 | false | false |
8 | N | 8,000 | MALETHA | 2024-04-03 | null | Hot/Dry Season | 2567 Tabaung, Waning, 10 | false | false |
9 | B | 6,000 | MALETHA | 2024-04-03 | null | Hot/Dry Season | 2567 Tabaung, Waning, 10 | false | false |
10 | S | 1,000 | MALETHA | 2024-04-04 | Hot/Dry Season | 2567 Tabaung, Waning, 11 | false | false | |
11 | N | 8,000 | MALETHA | 2024-04-04 | Hot/Dry Season | 2567 Tabaung, Waning, 11 | false | false | |
12 | B | 7,000 | MALETHA | 2024-04-04 | Hot/Dry Season | 2567 Tabaung, Waning, 11 | false | false | |
13 | S | 1,000 | MALETHA | 2024-04-05 | Hot/Dry Season | 2567 Tabaung, Waning, 12 | true | false | |
14 | N | 12,000 | MALETHA | 2024-04-05 | Hot/Dry Season | 2567 Tabaung, Waning, 12 | true | false | |
15 | B | 9,000 | MALETHA | 2024-04-05 | Hot/Dry Season | 2567 Tabaung, Waning, 12 | true | false | |
16 | S | 4,000 | MALETHA | 2024-04-06 | Before Thingyan | Hot/Dry Season | 2567 Tabaung, Waning, 13 | true | true |
17 | N | 15,000 | MALETHA | 2024-04-06 | Before Thingyan | Hot/Dry Season | 2567 Tabaung, Waning, 13 | true | true |
18 | B | 10,000 | MALETHA | 2024-04-06 | Before Thingyan | Hot/Dry Season | 2567 Tabaung, Waning, 13 | true | true |
19 | S | 1,000 | MALETHA | 2024-04-08 | Before Thingyan | Hot/Dry Season | 2567 Late_Tagu, Waxing, 0 | false | false |
20 | N | 10,000 | MALETHA | 2024-04-08 | Before Thingyan | Hot/Dry Season | 2567 Late_Tagu, Waxing, 0 | false | false |
21 | B | 5,000 | MALETHA | 2024-04-08 | Before Thingyan | Hot/Dry Season | 2567 Late_Tagu, Waxing, 0 | false | false |
22 | S | 2,000 | MALETHA | 2024-04-09 | Before Thingyan | Hot/Dry Season | 2567 Late_Tagu, Waxing, 1 | false | false |
23 | N | 15,000 | MALETHA | 2024-04-09 | Before Thingyan | Hot/Dry Season | 2567 Late_Tagu, Waxing, 1 | false | false |
24 | B | 10,000 | MALETHA | 2024-04-09 | Before Thingyan | Hot/Dry Season | 2567 Late_Tagu, Waxing, 1 | false | false |
25 | S | 2,000 | MALETHA | 2024-04-10 | Before Thingyan | Hot/Dry Season | 2567 Late_Tagu, Waxing, 2 | false | false |
26 | N | 10,500 | MALETHA | 2024-04-10 | Before Thingyan | Hot/Dry Season | 2567 Late_Tagu, Waxing, 2 | false | false |
27 | B | 1,800 | MALETHA | 2024-04-10 | Before Thingyan | Hot/Dry Season | 2567 Late_Tagu, Waxing, 2 | false | false |
28 | S | 1,000 | MALETHA | 2024-04-11 | Before Thingyan | Hot/Dry Season | 2567 Late_Tagu, Waxing, 3 | false | false |
29 | N | 13,000 | MALETHA | 2024-04-11 | Before Thingyan | Hot/Dry Season | 2567 Late_Tagu, Waxing, 3 | false | false |
30 | B | 9,000 | MALETHA | 2024-04-11 | Before Thingyan | Hot/Dry Season | 2567 Late_Tagu, Waxing, 3 | false | false |
31 | S | 2,000 | MALETHA | 2024-04-17 | After Thingyan | Hot/Dry Season | 2567 Tagu, Waxing, 9 | false | false |
32 | N | 15,000 | MALETHA | 2024-04-17 | After Thingyan | Hot/Dry Season | 2567 Tagu, Waxing, 9 | false | false |
33 | B | 10,000 | MALETHA | 2024-04-17 | After Thingyan | Hot/Dry Season | 2567 Tagu, Waxing, 9 | false | false |
34 | S | 2,000 | MALETHA | 2024-04-18 | After Thingyan | Hot/Dry Season | 2567 Tagu, Waxing, 10 | false | false |
35 | N | 13,000 | MALETHA | 2024-04-18 | After Thingyan | Hot/Dry Season | 2567 Tagu, Waxing, 10 | false | false |
36 | B | 10,000 | MALETHA | 2024-04-18 | After Thingyan | Hot/Dry Season | 2567 Tagu, Waxing, 10 | false | false |
37 | S | 2,000 | MALETHA | 2024-04-19 | After Thingyan | Hot/Dry Season | 2567 Tagu, Waxing, 11 | false | false |
38 | N | 10,000 | MALETHA | 2024-04-19 | After Thingyan | Hot/Dry Season | 2567 Tagu, Waxing, 11 | false | false |
39 | B | 8,000 | MALETHA | 2024-04-19 | After Thingyan | Hot/Dry Season | 2567 Tagu, Waxing, 11 | false | false |
40 | S | 2,000 | MALETHA | 2024-04-20 | After Thingyan | Hot/Dry Season | 2567 Tagu, Waxing, 12 | true | false |
41 | N | 10,000 | MALETHA | 2024-04-20 | After Thingyan | Hot/Dry Season | 2567 Tagu, Waxing, 12 | true | false |
42 | B | 9,000 | MALETHA | 2024-04-20 | After Thingyan | Hot/Dry Season | 2567 Tagu, Waxing, 12 | true | false |
43 | S | 3,000 | MALETHA | 2024-04-21 | After Thingyan | Hot/Dry Season | 2567 Tagu, Waxing, 13 | true | true |
44 | N | 12,000 | MALETHA | 2024-04-21 | After Thingyan | Hot/Dry Season | 2567 Tagu, Waxing, 13 | true | true |
45 | B | 11,000 | MALETHA | 2024-04-21 | After Thingyan | Hot/Dry Season | 2567 Tagu, Waxing, 13 | true | true |
46 | S | 2,000 | MALETHA | 2024-04-23 | null | Hot/Dry Season | 2567 Tagu, Waning, 0 | false | false |
47 | N | 8,500 | MALETHA | 2024-04-23 | null | Hot/Dry Season | 2567 Tagu, Waning, 0 | false | false |
48 | B | 8,000 | MALETHA | 2024-04-23 | null | Hot/Dry Season | 2567 Tagu, Waning, 0 | false | false |
49 | S | 1,500 | MALETHA | 2024-04-24 | null | Hot/Dry Season | 2567 Tagu, Waning, 1 | false | false |
50 | N | 5,000 | MALETHA | 2024-04-24 | null | Hot/Dry Season | 2567 Tagu, Waning, 1 | false | false |
51 | B | 5,000 | MALETHA | 2024-04-24 | null | Hot/Dry Season | 2567 Tagu, Waning, 1 | false | false |
52 | S | 2,000 | MALETHA | 2024-04-25 | null | Hot/Dry Season | 2567 Tagu, Waning, 2 | false | false |
53 | N | 8,500 | MALETHA | 2024-04-25 | null | Hot/Dry Season | 2567 Tagu, Waning, 2 | false | false |
54 | B | 6,000 | MALETHA | 2024-04-25 | null | Hot/Dry Season | 2567 Tagu, Waning, 2 | false | false |
55 | S | 2,000 | MALETHA | 2024-04-26 | null | Hot/Dry Season | 2567 Tagu, Waning, 3 | false | false |
56 | N | 7,000 | MALETHA | 2024-04-26 | null | Hot/Dry Season | 2567 Tagu, Waning, 3 | false | false |
57 | B | 5,000 | MALETHA | 2024-04-26 | null | Hot/Dry Season | 2567 Tagu, Waning, 3 | false | false |
58 | S | 2,000 | MALETHA | 2024-04-27 | null | Hot/Dry Season | 2567 Tagu, Waning, 4 | false | false |
59 | N | 11,000 | MALETHA | 2024-04-27 | null | Hot/Dry Season | 2567 Tagu, Waning, 4 | false | false |
60 | B | 10,000 | MALETHA | 2024-04-27 | null | Hot/Dry Season | 2567 Tagu, Waning, 4 | false | false |
61 | S | 5,000 | MALETHA | 2024-04-28 | null | Hot/Dry Season | 2567 Tagu, Waning, 5 | true | false |
62 | N | 13,000 | MALETHA | 2024-04-28 | null | Hot/Dry Season | 2567 Tagu, Waning, 5 | true | false |
63 | B | 11,000 | MALETHA | 2024-04-28 | null | Hot/Dry Season | 2567 Tagu, Waning, 5 | true | false |
64 | S | 3,000 | MALETHA | 2024-05-01 | null | Hot/Dry Season | 2567 Tagu, Waning, 8 | false | false |
65 | N | 11,000 | MALETHA | 2024-05-01 | null | Hot/Dry Season | 2567 Tagu, Waning, 8 | false | false |
66 | B | 9,000 | MALETHA | 2024-05-01 | null | Hot/Dry Season | 2567 Tagu, Waning, 8 | false | false |
67 | S | 3,000 | MALETHA | 2024-05-02 | null | Hot/Dry Season | 2567 Tagu, Waning, 9 | false | false |
68 | N | 13,000 | MALETHA | 2024-05-02 | null | Hot/Dry Season | 2567 Tagu, Waning, 9 | false | false |
69 | B | 10,000 | MALETHA | 2024-05-02 | null | Hot/Dry Season | 2567 Tagu, Waning, 9 | false | false |
70 | S | 6,000 | MALETHA | 2024-05-03 | null | Hot/Dry Season | 2567 Tagu, Waning, 10 | false | false |
71 | N | 15,000 | MALETHA | 2024-05-03 | null | Hot/Dry Season | 2567 Tagu, Waning, 10 | false | false |
72 | B | 12,000 | MALETHA | 2024-05-03 | null | Hot/Dry Season | 2567 Tagu, Waning, 10 | false | false |
73 | S | 5,000 | MALETHA | 2024-05-04 | null | Hot/Dry Season | 2567 Tagu, Waning, 11 | true | false |
74 | N | 13,000 | MALETHA | 2024-05-04 | null | Hot/Dry Season | 2567 Tagu, Waning, 11 | true | false |
75 | B | 13,000 | MALETHA | 2024-05-04 | null | Hot/Dry Season | 2567 Tagu, Waning, 11 | true | false |
76 | S | 5,000 | MALETHA | 2024-05-05 | null | Hot/Dry Season | 2567 Tagu, Waning, 12 | true | true |
77 | N | 15,000 | MALETHA | 2024-05-05 | null | Hot/Dry Season | 2567 Tagu, Waning, 12 | true | true |
78 | B | 10,000 | MALETHA | 2024-05-05 | null | Hot/Dry Season | 2567 Tagu, Waning, 12 | true | true |
79 | S | 5,000 | MALETHA | 2024-05-07 | null | Hot/Dry Season | 2567 Kason, Waxing, 0 | false | false |
80 | N | 16,000 | MALETHA | 2024-05-07 | null | Hot/Dry Season | 2567 Kason, Waxing, 0 | false | false |
81 | B | 13,000 | MALETHA | 2024-05-07 | null | Hot/Dry Season | 2567 Kason, Waxing, 0 | false | false |
82 | S | 2,000 | MALETHA | 2024-05-08 | null | Hot/Dry Season | 2567 Kason, Waxing, 1 | false | false |
83 | N | 12,000 | MALETHA | 2024-05-08 | null | Hot/Dry Season | 2567 Kason, Waxing, 1 | false | false |
84 | B | 10,000 | MALETHA | 2024-05-08 | null | Hot/Dry Season | 2567 Kason, Waxing, 1 | false | false |
85 | S | 4,000 | MALETHA | 2024-05-09 | null | Hot/Dry Season | 2567 Kason, Waxing, 2 | false | false |
86 | N | 15,000 | MALETHA | 2024-05-09 | null | Hot/Dry Season | 2567 Kason, Waxing, 2 | false | false |
87 | B | 15,000 | MALETHA | 2024-05-09 | null | Hot/Dry Season | 2567 Kason, Waxing, 2 | false | false |
88 | S | 5,000 | MALETHA | 2024-05-10 | null | Hot/Dry Season | 2567 Kason, Waxing, 3 | false | false |
89 | N | 20,000 | MALETHA | 2024-05-10 | null | Hot/Dry Season | 2567 Kason, Waxing, 3 | false | false |
90 | B | 20,000 | MALETHA | 2024-05-10 | null | Hot/Dry Season | 2567 Kason, Waxing, 3 | false | false |
91 | S | 5,000 | MALETHA | 2024-05-11 | null | Hot/Dry Season | 2567 Kason, Waxing, 4 | false | false |
92 | N | 20,000 | MALETHA | 2024-05-11 | null | Hot/Dry Season | 2567 Kason, Waxing, 4 | false | false |
93 | B | 20,000 | MALETHA | 2024-05-11 | null | Hot/Dry Season | 2567 Kason, Waxing, 4 | false | false |
94 | S | 5,000 | MALETHA | 2024-05-12 | null | Hot/Dry Season | 2567 Kason, Waxing, 5 | true | false |
95 | N | 20,000 | MALETHA | 2024-05-12 | null | Hot/Dry Season | 2567 Kason, Waxing, 5 | true | false |
96 | B | 20,000 | MALETHA | 2024-05-12 | null | Hot/Dry Season | 2567 Kason, Waxing, 5 | true | false |
97 | S | 5,000 | MALETHA | 2024-05-13 | null | Hot/Dry Season | 2567 Kason, Waxing, 6 | true | true |
98 | N | 22,000 | MALETHA | 2024-05-13 | null | Hot/Dry Season | 2567 Kason, Waxing, 6 | true | true |
99 | B | 20,000 | MALETHA | 2024-05-13 | null | Hot/Dry Season | 2567 Kason, Waxing, 6 | true | true |
100 | S | 5,000 | MALETHA | 2024-05-15 | null | Hot/Dry Season | 2567 Kason, Waxing, 8 | false | false |
Betel Leaf Prices — Nan Witt Yee Market, MaLeTha Village, Myanmar
Daily betel leaf market prices from the Nan Witt Yee market in MaLeTha Village, Ayadaw Township, Sagaing Region, Myanmar, covering 2024-04-01 to 2026-03-20. Each day includes three price observations, one per leaf grade (Small / Normal / Big), along with calendar, seasonal, and festival context. The Market column value MALETHA refers to the village, not the market's proper name.
Full methodology, validation, and figures are documented in the accompanying paper, archived on Zenodo: 10.5281/zenodo.20390228.
Dataset Details
- Rows: 1,800
- Market: Nan Witt Yee market, MaLeTha Village, Ayadaw Township, Sagaing Region (single market)
- Date range: 2024-04-01 – 2026-03-20
- Price unit: Myanmar Kyat per viss (MMK/viss)
- License: CC-BY-4.0
Data Collection
Collected from the market owner's handwritten daily paper transaction ledgers and manually transcribed into a spreadsheet. Where multiple prices were recorded for the same leaf grade on the same day, the average was used as that day's representative price. Random samples were cross-checked against the original paper records, and logical validation (positive prices, in-range dates, standardized categories) was applied during cleaning.
Dataset Structure
| Column | Type | Description |
|---|---|---|
ID |
int | Row identifier |
Type |
string | Leaf grade: S = Small, N = Normal, B = Big |
Price |
int | Market price in MMK per viss for that grade on that date |
Market |
string | Village name (MALETHA for all rows); the actual market is Nan Witt Yee |
Date |
date (YYYY-MM-DD) |
Gregorian calendar date |
Festival |
string | Nearby Myanmar festival window, if any (e.g. Before Thingyan, After Thadingyut, Before Tazaungdaing); blank if none |
Season |
string | Myanmar seasonal period: Hot/Dry Season, Rainy/Monsoon Season, Cool/Dry Season |
burmese_date |
string | Corresponding traditional Myanmar calendar date (e.g. 2567 Tabaung, Waning, 8) |
before_sabbath_eva |
bool | Whether the date falls on the eve before a Buddhist sabbath (Uposatha) day |
after_sabbath_eva |
bool | Whether the date falls the day after a Buddhist sabbath (Uposatha) day |
Leaf grade distribution
Each grade (S, N, B) has exactly 600 observations, one per date across the full date range.
Price summary
- Min: 100 MMK/viss
- Max: 32,000 MMK/viss
- Mean: ~6,739 MMK/viss
Median price by season: Cool/Dry 11,000 · Hot/Dry 4,000 · Rainy/Monsoon 2,000 (MMK/viss). Median price by grade: Normal 8,000 · Big 5,000 · Small 2,000 (MMK/viss).
Data Instance
ID,Type,Price,Market,Date,Festival,Season,burmese_date,before_sabbath_eva,after_sabbath_eva
1,S,2000,MALETHA,2024-04-01,,Hot/Dry Season,"2567 Tabaung, Waning, 8",False,False
Usage
With datasets:
from datasets import load_dataset
ds = load_dataset("aungthuhein-dev/betel-leaf", split="train")
print(ds[0])
# {'ID': 1, 'Type': 'S', 'Price': 2000, 'Market': 'MALETHA', 'Date': '2024-04-01',
# 'Festival': None, 'Season': 'Hot/Dry Season', 'burmese_date': '2567 Tabaung, Waning, 8',
# 'before_sabbath_eva': False, 'after_sabbath_eva': False}
With pandas:
import pandas as pd
df = pd.read_csv("hf://datasets/aungthuhein-dev/betel-leaf/betel_leaf_prices.csv")
df["Date"] = pd.to_datetime(df["Date"])
# Average price by leaf grade
print(df.groupby("Type")["Price"].mean())
Intended Use
Useful for price trend analysis, time-series forecasting, and studying the relationship between betel leaf prices and Myanmar-specific calendar factors (festivals, seasons, and the traditional lunar calendar). Intended for academic, research, educational, and non-commercial community use.
Limitations & Scope
- Single market, single crop. This covers only the Nan Witt Yee market in MaLeTha Village — it does not represent regional or national betel leaf prices.
- ~1,800 rows. Sufficient for classical time-series/regression methods; too small on its own for training large deep-learning models.
- No external market drivers. No transport cost, fuel price, or exchange-rate data is included beyond the season/festival/sabbath labels.
- Manually transcribed from paper ledgers. Validated via random cross-checks and logical rules (positive prices, in-range dates), but originates from handwritten records rather than machine-logged transactions.
Source
Collected from the Nan Witt Yee betel leaf market owner's daily paper transaction records, MaLeTha Village, Ayadaw Township, Sagaing Region, Myanmar.
Citation
If you use this dataset, please cite the accompanying paper:
@misc{hein2026betelleaf,
author = {Aung Thu Hein},
title = {Market Price Dataset for Betel Leaves Across Seasonal Trading Periods in Myanmar},
year = {2026},
publisher = {Zenodo},
doi = {10.5281/zenodo.20390228},
url = {https://doi.org/10.5281/zenodo.20390228}
}
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