py11. Frequency table in Python

The csv file is downloaded from http://countrylist.net/en/. The delimiter is a semicolon and not a comma.

According to the file, there are 3 countries in Antarctica.

The groupby function is used to organize the data under the category of 'continent'. We are usually are only interested in the 'name' column.

# ex11.py
from __future__ import division, print_function
from pandas import read_table
df = read_table('2015-02-07.dump.countrylist.net.csv',
                sep = ';') 
print('\n***The columns are')
for i in df.columns: print(i)
print('\n\n***There are %d rows.' % len(df))
print('\n***Countries in Antartica:')
df1 = df[df['continent'] == 'Antarctica']
print(df1['name'])
group = df.groupby('continent')
print('\n\n***Frequency table:')
print(group.count()['name'])
#***The columns are
#id
#continent
#name
#capital
#iso-2
#iso-3
#ioc
#tld
#currency
#phone
#utc
#wiki
#name_de
#capital_de
#wiki_de
#
#
#***There are 250 rows.
#
#***Countries in Antartica:
#10                     Antarctica
#32                  Bouvet Island
#64    French Southern Territories
#Name: name, dtype: object
#
#
#***Frequency table:
#continent
#Africa           62
#Antarctica        3
#Asia             55
#Australia        26
#Europe           53
#North America    31
#South America    20
#Name: name, dtype: int64