Exchange Rates: Monthly Average

Last updated: 30 Sept 2026

Monthly average ringgit exchange rates against major currencies. Sample fixture for frontend development. Values are illustrative, not official BNM rates.

1,440 rows × 5 cols

datecurrencybuyingmiddleselling
01 Sept 2026USD4.22714.23134.2355
01 Sept 2026SGD3.28333.28663.2899
01 Sept 2026EUR4.95004.95504.9600
01 Sept 2026GBP5.68305.68875.6944
01 Sept 2026CNY0.59240.59300.5936
01 Sept 2026JPY0.02860.02860.0286
01 Aug 2026USD4.20594.21014.2143
01 Aug 2026SGD3.26683.27013.2734
01 Aug 2026EUR4.92524.93014.9350
01 Aug 2026GBP5.65455.66025.6659
01 Aug 2026CNY0.58940.59000.5906
01 Aug 2026JPY0.02850.02850.0285
01 Jul 2026USD4.18464.18884.1930
01 Jul 2026SGD3.25023.25353.2568
01 Jul 2026EUR4.90034.90524.9101
01 Jul 2026GBP5.62595.63155.6371
01 Jul 2026CNY0.58640.58700.5876
01 Jul 2026JPY0.02840.02840.0284
01 Jun 2026USD4.18284.18704.1912
01 Jun 2026SGD3.24883.25213.2554
01 Jun 2026EUR4.89814.90304.9079
01 Jun 2026GBP5.62355.62915.6347
01 Jun 2026CNY0.58620.58680.5874
01 Jun 2026JPY0.02830.02830.0283
01 May 2026USD4.20214.20634.2105
01 May 2026SGD3.26383.26713.2704
01 May 2026EUR4.92084.92574.9306
01 May 2026GBP5.64945.65515.6608
01 May 2026CNY0.58890.58950.5901
01 May 2026JPY0.02850.02850.0285
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Download (1,440 rows × 5 columns)

FormatSizeDownloadLink
Parquet25 KB
CSV59 KB
Excel42 KB

Programmatic Access

import pandas as pd

URL = "https://data.bnm.gov.my/dataset/exchange-rates-monthly.parquet"

df = pd.read_parquet(URL)
print(df.shape)   # (1440, 5)
print(df.dtypes)
df

Cite

Please cite this dataset as follows.

APA

Malaysia, B. N. (2026). Exchange Rates: Monthly Average. BNM Open Data.

Harvard

Malaysia, B.N. 2026, Exchange Rates: Monthly Average. BNM Open Data.

MLA

Malaysia, Bank Negara. "Exchange Rates: Monthly Average." BNM Open Data (2026).

Chicago

Malaysia, Bank Negara. "Exchange Rates: Monthly Average." BNM Open Data (2026).

BibTeX

@misc{bnm_exchange_rates_monthly,
  author  = {Malaysia, Bank Negara},
  title   = {Exchange Rates: Monthly Average},
  journal = {BNM Open Data},
  year    = {2026}
}