<jupyter_start><jupyter_text>Basic descriptive statistcsUsing pandas and numpy, we can do basic statistics.<jupyter_code>import pandas as pd
import numpy as np

data_frame = pd.read_csv("../../data/short_table.csv", delimiter=',')

# show it
data_frame<jupyter_output><empty_output><jupyter_text>You can _take_ a column out of the DataFrame. In this context it works like a Python dictionary.<jupyter_code>data_frame["area"]<jupyter_output><empty_output><jupyter_text>Even though this data structure appears more than just a vector, numpy is capable of applying basic descriptive statistics functions:<jupyter_code>np.mean(data_frame["area"])
np.min(data_frame["area"])
np.max(data_frame["area"])<jupyter_output><empty_output><jupyter_text>Individual cells of the DataFrame can be accessed like this:<jupyter_code>data_frame["area"][0]<jupyter_output><empty_output><jupyter_text>For loops can also iterate over table columns like this:<jupyter_code>for area_value in data_frame["area"]:
    print(area_value)<jupyter_output>45
23
68
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