ktl014
8/10/2017 - 7:09 AM

Understanding your data from: https://campus.datacamp.com/courses/kaggle-python-tutorial-on-machine-learning/getting-started-with-python?ex=

Understanding your data from: https://campus.datacamp.com/courses/kaggle-python-tutorial-on-machine-learning/getting-started-with-python?ex=3

pd_describe.txt
content_copyfile_download
Before starting with the actual analysis, it's important to understand the structure of your data. Both test and train are DataFrame objects, the way pandas represent datasets. You can easily explore a DataFrame using the .describe() method. .describe() summarizes the columns/features of the DataFrame, including the count of observations, mean, max and so on. Another useful trick is to look at the dimensions of the DataFrame. This is done by requesting the .shape attribute of your DataFrame object. (ex. your_data.shape)

train.describe()
test.describe()

train.shape
test.shape