<jupyter_start><jupyter_text>Python Pandas<jupyter_code>filename = "students.csv"<jupyter_output><empty_output><jupyter_text>1.    Learn to use Pandas to read in CSV file 2.    Find out how many rows and columns in this dataset. 3.   Check that data types of each columns is handled by Pandas (automatically)  Let's learn about Pandas Data Structures*    Series*    DataFrame  Pandas Series*   String/Text Values*   Integer/Number Values<jupyter_code>names = ["sally", "dave", "john", "dylan", "joey", "anne"]
cca = ["basketball", "NCC", "NCC", "basketball", "red cross", "robotics"]

year = [2010, 2011, 2012, 2013, 2014, 2015]
height = [150, 151, 151, 153, 154, 156]<jupyter_output><empty_output><jupyter_text>Plot Line Graphs and Bar Graphs for Pandas Series  Pie Charts ideal for Categorical Data Values for example Gender, Nationality<jupyter_code>gender = "F", "M", "M", "M", "F", "F"]
nationality = ["Singaporean", "Korean", "Japanese", "Singaporean", "Japanese", "Singaporean"]<jupyter_output><empty_output><jupyter_text>Histogram ideal for Age Groups<jupyter_code>age = [10, 20, 14, 22, 24, 12]<jupyter_output><empty_output><jupyter_text>Box Plots ideal for Test Scores and GPA<jupyter_code>scores = [60, 89, 90, 92, 60, 75]
gpa = [3.0, 3.1, 3.9, 4.0, 3.3, 3.5]<jupyter_output><empty_output>
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