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Complete the Pandas modules, do the exercises, take the exam, and you will become w3schools certified!
A Pandas DataFrame is a 2 dimensional data structure, like a 2 dimensional array, or a table with rows and columns.
Pandas is a Python library used for working with data sets. It has functions for analyzing, cleaning, exploring, and manipulating data. The name "Pandas" has a reference to both "Panel Data", and "Python Data Analysis" and was created by Wes McKinney in 2008.
Complete the Pandas modules, do the exercises, take the exam, and you will become w3schools certified!
A simple way to store big data sets is to use CSV files (comma separated files). CSV files contains plain text and is a well know format that can be read by everyone including Pandas. In our examples we will be using a CSV file called 'data.csv'. Download data.csv. or Open data.csv.
Scatter Plot. Specify that you want a scatter plot with the. kind argument: kind = 'scatter'. A scatter plot needs an x- and a y-axis. In the example below we will use "Duration" for the x-axis and "Calories" for the y-axis. Include the x and y arguments like this: x = 'Duration', y = 'Calories'.
Complete the Pandas modules, do the exercises, take the exam, and you will become w3schools certified!
df.loc[["Sally", "John"]] Specify columns by including their labels in another list: df.loc[["Sally", "John"], ["age", "qualified"]] You can also specify a slice of the DataFrame with from and to labels, separated by a colon: df.loc["Sally": "John"] ;0.
NumPy is a Python library. NumPy is used for working with arrays. NumPy is short for "Numerical Python".
Definition and Usage. The merge() method updates the content of two DataFrame by merging them together, using the specified method (s). Use the parameters to control which values to keep and which to replace.
