arche
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scrapinghub
Analyze scraped data
~I added a subclass for DataFrame, in order to override its `to_html()`, allowing us to define some defaults styling, like the clickable URLs from #76 .~ I changed my approach...
If the main section is too big, there's a huge blank space after plots. @simoess
Say, we scrape one website from different categories. In this case all items will have the same root, e.g. https://pandas.pydata.org/pandas-docs/stable/categorical.html https://pandas.pydata.org/pandas-docs/stable/merging.html have `https://pandas.pydata.org/pandas-docs/stable/` in common. By returning this information, we...
https://github.com/scrapinghub/gatf/pull/237#pullrequestreview-206687741 Since it's so fast, we can simplify people's life.
The current logic of dividing on batches by start_index and count doesn't account for `filter`. When using `filter`, returned items `_key` don't correspond with actual index so the data repeats.
The graph data is displayed from bottom to top, the legend starts from the top to the bottom. Also it'd be nice to have column labels in the legend. ![Screenshot...
It will be really convenient to have clickable urls, as opposing to manually copying them and opening a page each time. It will save time. As far as I remember...
They contain repeating parts, so why not make code simpler.