Dataset: IDX 30 Stocks Price Time Series

About this Dataset

IDX 30 Stocks Price Time Series

Context

Ever since I joined Kaggle, I have been spoilt with countless of high quality datasets and notebooks from many experienced people. I have decided to upload my very first dataset, in order to learn how to upload dataset in Kaggle, as well as an attempt at giving back to the community.

This dataset contains historical price data of Indonesia IDX 30 Stocks. As the list keeps changing, I am using the latest information as of the writing of this text (16 March 2022).
Recent changes include removal of 2 large tobacco companies from the IDX 30, which are HMSP (H.M. Sampoerna), and GGRM (Gudang Garam).

Source of IDX 30 Stocks list:
https://www.kontan.co.id/indeks-idx30

Content

The dataset consists of 30 csv files. Each csv file contains different stock historical price, with different ticker symbol. The data is obtained using pandas datareader, from Yahoo finance.

As the list of the IDX 30 companies are everchanging, it might include young companies which has undergone recent IPO (such as Bukalapak with ticker symbol BUKA, an E-commerce startup). Hence, despite the data filter indicating starting time of 2006, different companies have different data starting point.

I chose 2006 as data starting point in order to capture the 2008 financial crisis in the data, as well as giving some buffer time before the 2008 market crash.

CSV file formats are as follows:

Index:
Date - datetime64 datatype, with format of YYYY-MM-DD (eg: 2008-07-21). Data granularity is daily, and the date excludes days where market is closed. (eg: weekends and public holidays)

Columns descriptions (Price in IDR, as you might have noticed from the number of digits):
High - Highest price reached in the day
Low - Lowest price reached in the day
Open - Price of the stock at market open
Close - Price of the stock at market close
Volume - Number of stocks traded during the day
Adj Close - Price of the stock at market close, adjusted (eg: due to stock splits)

Acknowledgements

My inspiration comes from szrlee which has provided DJIA 30 Stock Time Series. Thank you for the inspiration and sharing of your dataset and how to use pandas datareader.
Link to his dataset:
https://www.kaggle.com/szrlee/stock-time-series-20050101-to-20171231

Special thanks to Yahoo finance, creator of Pandas-datareader, Kaggle team. Lastly, thank you all members of the Kaggle community, who has provided endless inspirations and wealth of knowledge, as well as continually reminding me how dumb and inexperienced I am as a member of this data community. It drives me to improve myself.

Inspiration

As I am relatively new to stock trading, and currently only has access to the Indonesian stock market, I would love to see anyone giving insights to how the companies behave in comparison with other stocks in different markets. Please note that even some of the largest stocks in Indonesia are merely penny stocks in other markets such as US. (All Indonesian stocks market cap combined is roughly equals to half of Apple's market cap).

Tables

Adro 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.adro_2006_01_01_to_2022_03_16

94.62 KB
3380 rows
7 columns


CREATE TABLE adro_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Antm 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.antm_2006_01_01_to_2022_03_16

118.1 KB
4017 rows
7 columns


CREATE TABLE antm_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Asii 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.asii_2006_01_01_to_2022_03_16

117.14 KB
4017 rows
7 columns


CREATE TABLE asii_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Bbca 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.bbca_2006_01_01_to_2022_03_16

121.56 KB
4018 rows
7 columns


CREATE TABLE bbca_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Bbni 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.bbni_2006_01_01_to_2022_03_16

87.26 KB
4014 rows
7 columns


CREATE TABLE bbni_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Bbri 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.bbri_2006_01_01_to_2022_03_16

115.48 KB
4017 rows
7 columns


CREATE TABLE bbri_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Bbtn 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.bbtn_2006_01_01_to_2022_03_16

86.08 KB
3035 rows
7 columns


CREATE TABLE bbtn_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Bmri 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.bmri_2006_01_01_to_2022_03_16

114.96 KB
4017 rows
7 columns


CREATE TABLE bmri_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Brpt 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.brpt_2006_01_01_to_2022_03_16

118.65 KB
4018 rows
7 columns


CREATE TABLE brpt_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Buka 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.buka_2006_01_01_to_2022_03_16

10.18 KB
152 rows
7 columns


CREATE TABLE buka_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" BIGINT,
  "low" BIGINT,
  "open" BIGINT,
  "close" BIGINT,
  "volume" BIGINT,
  "adj_close" BIGINT
);

Cpin 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.cpin_2006_01_01_to_2022_03_16

114.48 KB
3970 rows
7 columns


CREATE TABLE cpin_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Emtk 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.emtk_2006_01_01_to_2022_03_16

69.23 KB
3023 rows
7 columns


CREATE TABLE emtk_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Excl 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.excl_2006_01_01_to_2022_03_16

109.55 KB
4008 rows
7 columns


CREATE TABLE excl_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Icbp 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.icbp_2006_01_01_to_2022_03_16

111.6 KB
4017 rows
7 columns


CREATE TABLE icbp_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Inco 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.inco_2006_01_01_to_2022_03_16

115.16 KB
4015 rows
7 columns


CREATE TABLE inco_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Indf 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.indf_2006_01_01_to_2022_03_16

105.27 KB
4016 rows
7 columns


CREATE TABLE indf_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Inkp 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.inkp_2006_01_01_to_2022_03_16

111.45 KB
4016 rows
7 columns


CREATE TABLE inkp_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Klbf 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.klbf_2006_01_01_to_2022_03_16

106.78 KB
4018 rows
7 columns


CREATE TABLE klbf_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Mdka 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.mdka_2006_01_01_to_2022_03_16

48.76 KB
1680 rows
7 columns


CREATE TABLE mdka_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Mika 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.mika_2006_01_01_to_2022_03_16

49.3 KB
1738 rows
7 columns


CREATE TABLE mika_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Pgas 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.pgas_2006_01_01_to_2022_03_16

109.55 KB
4016 rows
7 columns


CREATE TABLE pgas_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Ptba 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.ptba_2006_01_01_to_2022_03_16

111.6 KB
4017 rows
7 columns


CREATE TABLE ptba_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Smgr 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.smgr_2006_01_01_to_2022_03_16

113.94 KB
4014 rows
7 columns


CREATE TABLE smgr_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Tbig 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.tbig_2006_01_01_to_2022_03_16

77.73 KB
2829 rows
7 columns


CREATE TABLE tbig_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Tins 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.tins_2006_01_01_to_2022_03_16

118.91 KB
4016 rows
7 columns


CREATE TABLE tins_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Tlkm 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.tlkm_2006_01_01_to_2022_03_16

109.27 KB
4017 rows
7 columns


CREATE TABLE tlkm_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Towr 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.towr_2006_01_01_to_2022_03_16

73.61 KB
2984 rows
7 columns


CREATE TABLE towr_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Untr 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.untr_2006_01_01_to_2022_03_16

135.9 KB
4017 rows
7 columns


CREATE TABLE untr_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Unvr 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.unvr_2006_01_01_to_2022_03_16

120.69 KB
4018 rows
7 columns


CREATE TABLE unvr_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);

Wskt 2006–01–01 To 2022–03–16

@kaggle.rhesamulyadi_idx_30_stocks_price_history.wskt_2006_01_01_to_2022_03_16

71.43 KB
2296 rows
7 columns


CREATE TABLE wskt_2006_01_01_to_2022_03_16 (
  "date" TIMESTAMP,
  "high" DOUBLE,
  "low" DOUBLE,
  "open" DOUBLE,
  "close" DOUBLE,
  "volume" DOUBLE,
  "adj_close" DOUBLE
);