![]() Using the JSON API response we can parse through the data and append the date and pageviews to the dataframe we created above. df = pd.DataFrame(columns = ) Process Wiki JSON response We first create an empty dataframe with two columns, Date and Hits. To graph the results we need to store the data in a Pandas dataframe. Response = requests.request("GET", url, headers=headers, data=payload) Even HTML for debugging purposes.Īfter we build the API call we request it and load the JSON response into a JSON Python object to parse in the next bit. prop: Which properties to get for the queried pages.action: Which action to perform, there are dozens available here.Let me break down this API call we’re using: I know I have a few more tutorials in mind using other API parameters. The API for Wikipedia is actually quite extensive and I encourage you to explore it. In this tutorial’s example, we’re going to use “Olympic Games”. First, we’ll want to create a variable for our keyword or keyword phrase. Let’s now set up our API call to Wikipedia ( MediaWiki). import pandas as pdįrom pytrends.request import TrendReq Hit Wiki API Now we can import the needed modules at the top of our script. ![]() If you are using Google Colab put an exclamation mark at the beginning. pytrends: to interface with the Google Trends APIįirst, let’s install the PyTrends module which you won’t like have already.json: for processing Semrush API response.requests: for making API calls to Wikipedia.pandas: for storing and exporting results.Access to a Linux installation (I recommend Ubuntu) or Google Colab.Python 3 is installed and basic Python syntax understood. ![]()
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