HellO!?
Today I'm back with a new notebook which demonstrates a way of working with data in Jupyter.
Source file
I downloaded the dataset from
Kaggle a platform to find real-world data and connect with other data enthusiasts.
There you will find an incredible collection of datasets and projects and you can also participate in competitions.
Short evidence of the work
After I returned a concise summary of the dataframe I performed the cleaning of data, to get my data into a usable and consistent format for analysis
astype() method is used to convert a pandas object to a specified data type.
I used fillna(0) to get rid of the error that initially appeared. Try it yourself!
Where is the rest of the work? ?
You can find more in my GitHub repository. Here I uploaded the notebook and of course the dataset. In short words, you will learn how to
load a dataframe,
examine its metadata,
convert data types
explore the dataframe using iloc indexing.
More than that, you will learn about Boolean masking and...how to calculate the median value. ?
Are you ready to explore the data?
The above is the detailed content of Working with DataFrames in Pandas. For more information, please follow other related articles on the PHP Chinese website!
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