table.add_column("Annual Rainfall",[600.5, 1146.4, 1714.7, 619.5, 1214.8, 646.9,869.4])
print '=================================table===================================='
print table
def testFunc2(data='mycsv.csv'):
'''
从 csv 文件中加载数据
'''
mycsv=open(data)
table=from_csv(mycsv)
mycsv.close()
print
'===========================================table=============================================='
print table
print
'=================================table:SepalLength_Species===================================='
print table.get_string(fields=['SepalLength','Species'])
print '=======================================table:60=>80
rows======================================'
print table.get_string(start=60,end=80)
if __name__=='__main__':
testFunc1()
testFunc2(data='iris.csv')
结果如下：
=================================table====================================
+-----------+------+------------+-----------------+
| City name | Area | Population | Annual Rainfall |
+-----------+------+------------+-----------------+
| Adelaide | 1295 | 1158259 | 600.5 |
| Brisbane | 5905 | 1857594 | 1146.4 |
| Darwin | 112 | 120900 | 1714.7 |
| Hobart | 1357 | 205556 | 619.5 |
| Sydney | 2058 | 4336374 | 1214.8 |
| Melbourne | 1566 | 3806092 | 646.9 |
| Perth | 5386 | 1554769 | 869.4 |
+-----------+------+------------+-----------------+
=================================table====================================
+-----------+------+------------+-----------------+-----------+------+------------+-----------------+
| City name | Area | Population | Annual Rainfall | City name | Area | Population | Annual Rainfall |
+-----------+------+------------+-----------------+-----------+------+------------+-----------------+
| Adelaide | 1295 | 1158259 | 600.5 | Adelaide | 1295 | 1158259 | 600.5 |
| Brisbane | 5905 | 1857594 | 1146.4 | Brisbane | 5905 | 1857594 | 1146.4 |
| Darwin | 112 | 120900 | 1714.7 | Darwin | 112 | 120900 | 1714.7 |
| Hobart | 1357 | 205556 | 619.5 | Hobart | 1357 | 205556 | 619.5 |
| Sydney | 2058 | 4336374 | 1214.8 | Sydney | 2058 | 4336374 | 1214.8 |
| Melbourne | 1566 | 3806092 | 646.9 | Melbourne | 1566 | 3806092 | 646.9 |
| Perth | 5386 | 1554769 | 869.4 | Perth | 5386 | 1554769 | 869.4 |
+-----------+------+------------+-----------------+-----------+------+------------+-----------------+
===========================================table==============================================
+-----+-------------+------------+-------------+------------+------------+
| id | SepalLength | SepalWidth | PetalLength | PetalWidth | Species |
+-----+-------------+------------+-------------+------------+------------+
| 1 | 5.1 | 3.5 | 1.4 | 0.2 | setosa |
| 2 | 4.9 | 3 | 1.4 | 0.2 | setosa |
| 3 | 4.7 | 3.2 | 1.3 | 0.2 | setosa |
| 4 | 4.6 | 3.1 | 1.5 | 0.2 | setosa |
| 5 | 5 | 3.6 | 1.4 | 0.2 | setosa |
| 6 | 5.4 | 3.9 | 1.7 | 0.4 | setosa |
| 7 | 4.6 | 3.4 | 1.4 | 0.3 | setosa |
| 8 | 5 | 3.4 | 1.5 | 0.2 | setosa |
| 9 | 4.4 | 2.9 | 1.4 | 0.2 | setosa |
| 10 | 4.9 | 3.1 | 1.5 | 0.1 | setosa |
| 11 | 5.4 | 3.7 | 1.5 | 0.2 | setosa |
| 12 | 4.8 | 3.4 | 1.6 | 0.2 | setosa |
| 13 | 4.8 | 3 | 1.4 | 0.1 | setosa |
| 14 | 4.3 | 3 | 1.1 | 0.1 | setosa |
| 15 | 5.8 | 4 | 1.2 | 0.2 | setosa |
| 16 | 5.7 | 4.4 | 1.5 | 0.4 | setosa |
| 17 | 5.4 | 3.9 | 1.3 | 0.4 | setosa |
| 18 | 5.1 | 3.5 | 1.4 | 0.3 | setosa |
| 19 | 5.7 | 3.8 | 1.7 | 0.3 | setosa |
| 20 | 5.1 | 3.8 | 1.5 | 0.3 | setosa |
| 21 | 5.4 | 3.4 | 1.7 | 0.2 | setosa |
