Data Analysis & Processing with Pandas/

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Description

Description

The DataFrame provides many functions that show description operations, such as mean, median, and sum, that help you get a feel for the data.

We'll cover the following...

For these functions, the default operations are performed column-wise. If you want to do row-wise operations, you can pass the parameter axis=1 to those functions.

mean

Calculate the mean of column or row. In the code below, there is a function called describe() that gives you mean, count, minimum and maximum values, three quartiles, and the standard deviation. This is very useful when you are in exploratory data analysis.

Python 3.5
import pandas as pd
# create a matrix, the size is 10*3
d = {"a":range(1, 10), "b": range(11,20), "c": range(21,30)}
df = pd.DataFrame(d)
print("---------------------------")
# calculate the mean of each column
print("The mean of each column is {}".format(df.mean().values))
# calculate the mean of each row
print("The mean of each row is {}".format(df.mean(axis=1).values))
# give a summary of your data on column wise
print(df.describe())

Line 8 shows what happens when you call ...