<p>有条件地读取csv数据,捕获城市名称并将项目附加到本地列表中。然后,将该列表用于其他扩展需求,例如定义类和字典。你知道吗</p>
<pre><code>import csv
weatherdata = []
with open('WeatherData.csv'), 'r') as csvfile:
readCSV = csv.reader(csvfile)
for line in readCSV:
items = [i.replace('"', '').split() for i in line][0]
if len(items) < 3:
city = items
else:
weatherdata.append([' '.join(city)] + items)
for i in weatherdata:
print(i)
# ['New York', '2016-04-08T07:00Z', '6.2', 'd300', '1', '0.0', '220', '10.2', '79', '331']
# ['New York', '2016-04-08T08:00Z', '7.1', 'd000', '1', '0.0', '223', '10.6', '74', '400']
# ['New York', '2016-04-08T09:00Z', '7.7', 'd000', '1', '0.0', '225', '10.9', '68', '448']
# ['New York', '2016-04-08T10:00Z', '8.4', 'd000', '2', '0.0', '225', '10.9', '64', '553']
# ['New York', '2016-04-08T11:00Z', '8.9', 'd100', '5', '0.0', '226', '11.0', '59', '550']
# ['New York', '2016-04-08T12:00Z', '9.1', 'd100', '8', '0.0', '227', '11.0', '57', '516']
# ['New York', '2016-04-08T13:00Z', '8.6', 'd100', '1', '0.0', '227', '10.6', '61', '447']
# ['New York', '2016-04-08T14:00Z', '8.1', 'd100', '4', '0.0', '227', '10.1', '64', '362']
# ['Boston', '2016-04-08T07:00Z', '6.2', 'd300', '1', '0.0', '220', '10.2', '79', '331']
# ['Boston', '2016-04-08T08:00Z', '7.1', 'd000', '1', '0.0', '223', '10.6', '74', '400']
# ['Boston', '2016-04-08T09:00Z', '7.7', 'd000', '1', '0.0', '225', '10.9', '68', '448']
# ['Boston', '2016-04-08T10:00Z', '8.4', 'd000', '2', '0.0', '225', '10.9', '64', '553']
# ['Boston', '2016-04-08T11:00Z', '8.9', 'd100', '5', '0.0', '226', '11.0', '59', '550']
# ['Boston', '2016-04-08T12:00Z', '9.1', 'd100', '8', '0.0', '227', '11.0', '57', '516']
# ['Boston', '2016-04-08T13:00Z', '8.6', 'd100', '1', '0.0', '227', '10.6', '61', '447']
# ['Boston', '2016-04-08T14:00Z', '8.1', 'd100', '4', '0.0', '227', '10.1', '64', '362']
</code></pre>