Whatever your project size is, we will handle it well with all the standards fulfilled! We are here to give 100% satisfaction.
For job seekers, please visit our Career Page or send your resume to hr@actowizsolutions.com
This blog shows important Python libraries for scraping and processing information like pricing, IBAN, and date. It is difficult to process this data type; however, with proper libraries, you can easily do that.
It might look like an easy job to parse currencies, dates, and IBANs. However, think about all the different locales, combinations, and formats. It parses German or USA format dates, scraping decimal values of prices in USD, EUR, or Rupees. An easy job can initially can get very messy!
Fortunately, there are Python libraries that we can utilize rather than coding the rules ourselves.
It is part of preparing data, which is vital for all Machine Learning applications.
Suggested library — dateparser
Here, we parse a date in the German format; we could provide a hint of the library regarding the language for date formats:
d = dateparser.parse('2.Mai 2020', languages=['de'])
The results look great:
2020-05-02 00:00:00
We could try and pass all invalid dates to a library:
d = dateparser.parse('2.Abc 2020', languages=['de'])
Here, we would get such results that are ideal:
None
It’s time to parse the date without providing any hint about a language:
d = dateparser.parse('2020.12.8')
This works well also:
2020-12-08 00:00:00
Suggested library — price-parser
This could get more complicated with pricing parsing, just think about different currencies as well as different ways about how the pricing is written.
Let’s take a test using EUR price as well as comma like a decimal extractor:
p = Price.fromstring("-114,47 €")
The result - we find a number as well as currency symbol:
Price(amount=Decimal('-114.47'), currency='€')
Parse pricing in Russian rubles:
p = Price.fromstring("3 500 руб")
Price(amount=Decimal('11499'), currency='Rs')
Parse pricing in US dollars:
p = Price.fromstring("$1499.99")
Price(amount=Decimal('1499.99'), currency='$')
One more example, without any currency symbol, however with comma like a thousand extractor:
p = Price.fromstring("199,999.00")
The amount gets parsed appropriately:
Price(amount=Decimal('199999.00'), currency=None)
In case, we utilize the point like a decimal extractor:
p = Price.fromstring("199.999,00")
The results are correct also:
Price(amount=Decimal('199999.00'), currency=None)
Suggested library — schwifty
Test German IBAN number:
i = IBAN('DE89 3704 0044 0532 0130 00')
Country(alpha_2='DE', alpha_3='DEU', name='Germany', numeric='276', official_name='Federal Republic of Germany')
Test invalid IBAN:
try: i = IBAN('DE89 3704') print(i.country) except Exception as e: print(e)
Result like it might be anticipated in the case:
Invalid IBAN length
The step of data preparation is among the crucial steps in Machine Learning. Appropriate use of accessible libraries permits streamlining data processing. This blog teaches you how to procedure dates, currencies, and IBANs using web scraping services. For more details, contact Actowiz Solutions now!
Discover how Naver Data Scraping Services help businesses overcome market research challenges in South Korea with real-time, localized insights and trends.
Learn how Grocery Chain API Data Extraction can optimize inventory management by providing real-time stock updates, demand forecasting, and accurate product tracking.
An in-depth Decathlon 2024 sales analysis, exploring key trends, consumer behavior, revenue growth, and strategic insights for future success.
Explore cosmetic product API datasets for retail trends, ingredient analysis, and market insights to enhance business decisions in the beauty industry.
Discover how businesses used Grocery Store Location Datasets to identify high-potential areas, reduce expansion risks, and streamline retail growth strategies.
Explore how Naver Data Scraping Services help businesses analyze consumer behavior, track trends, and gain a competitive edge in South Korea's dynamic market.
Compare pricing, delivery speed, and seller insights on Flipkart, Amazon, and Meesho with Actowiz's marketplace intelligence tools. Stay ahead in 2025.
Extract real-time Best Buy data on pricing, features, and stock availability. Optimize decisions with web scraping insights. Learn more in our expert guide!