![]() DataGrip is a professional DataBase IDE and is a great tool for advanced data exploration and analytical queries for your data in MongoDB and Atlas. Tell us in the comments about any other topics you’d like us to cover in future tutorials.JetBrains released a new version of DataGrip that includes support for MongoDB and ships with the MongoDB Shell out of the box.Ī few months ago, JetBrains released the first version of DataGrip that supports MongoDB. We’ve tried to provide answers to many of the most common questions people have when they are just starting out with pandas. With df.describe we can get statistics on numeric columns data. The winner_age, loser_age, loser_rank, and winner_rank columns don’t have many NaN values, so we’ll replace the NaN values with a median number. In the minutes column we have 91% NaN values, so we’ll drop this column because it doesn’t contain any useful information. Now let’s find out whether there are NaN values in our DataFrame.ĭf.isna().any() is True when the column contains NaN values. We’ll drop any duplicates with pd.drop_duplicates, with inplace = True applying changes to the DataFrame. Let’s download the dataset with the tennis game results.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |