In this article, we’re going to look at extracting data from the YouTube Data API. For this, we need to setup an API key, which you can get via the Google Developer Console. Now, you […]
Category: Python
Scraping websites using rotated user agents & summarising the returned content
Scraping other websites is amazing – it’s a rich source of data that you don’t have to pay for, that you can use for some serious analysis. The problem is, websites may have provisions in […]
Pulling comment sentiment from Twitter API
In my last article, I spoke about extracting tweet data from Twitter, filtering it and cleaning it up. Today, I want to look at sentiment analysis of comments / replies to tweets using the API. […]
Extracting and cleaning data from the Twitter API in Python
I’ve heard from a tonne of people that they don’t read the news because it’s negative and the constant presence of articles about assault, killings and other terrible things bring their mood down. So I […]
A simple intro to sentiment analysis in Python
Sentiment analysis can provide key insight into the feelings of your customers towards your company & hence is becoming an increasingly important part of data analysis. Building a machine learning model to identify positive and […]
Working with date time features in your ML models
Having a date in our dataset can really improve our predictions. Imagine an ice cream company, their data has a seasonal aspect (more sales in summer), so predicting sales information without dates in our data […]
Statistical methods of handling outliers
Outliers can be a real pain & can skew our datasets. In the below, I’ve added an obvious outlier on row 3 (company name = Talane). If we were to take an average of InvoiceValue, […]
Wild Wednesday: handling semi structured JSON data
Wild Wednesday posts are all about taming semi or unstructured data. Today, we’re going to look at ingesting JSON data, generated from YARN, using the API; putting it into a dataframe and then outputting that […]
Toolset Tuesday: Plotting data from your Pandas Dataframes
In this Toolset Tuesday post, we’re going to look at some simple plotting in Plotly. Why? Because the first step validating that your Python script has output accurate data is visually sense-checking it. If you […]
