Depending on data source we might notice multiple duplicates in our dataset. The decision to remove duplicates should be based on the understanding of the domain. In most cases, duplicates come from errors in data collection process and it is recommended to remove them in order to reduce bias in our analysis, with the help of the following:
df = df.drop_duplicates(subset=['column_name'])
Knowing basic text cleaning techniques, we can now learn how to store the data in an efficient way. For this purpose, we will explain how to use one of the most convenient NoSQL databases—MongoDB.
Capture: Once you have made a connection to your API you need to make a special request and receive the data at your end. This step requires ...
