July 2017
Intermediate to advanced
398 pages
11h 54m
Chinese
Content preview from Python数据处理
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162
｜
第
8
章
def
zip_data(headers, data):
zipped_data = []
for
drow
in
data:
zipped_data.append(zip(headers, drow))
return
zipped_data
def
create_zipped_data(final_header_rows, data_rows, skip_index):
new_data = []
for
row
in
data_rows[1:]:
new_row = []
for
index, data
in
enumerate(row):
if
index
not in
skip_index:
new_row.append(data)
new_data.append(new_row)
zipped_data = zip_data(final_header_rows, new_data)
return
zipped_data
有了这些新函数，我们可以保存代码、清洗变量名，还可以利用辅助函数将标题与数据行
合并，并返回合并后的数据列表。代码更加清晰，分块也更加合理。我们继续将同样的逻
辑应用到文件中的其他代码。我们来看一下最终结果：
from
csv
import
reader
import
dataset
def
get_rows(file_name):
rdr = reader(open(file_name, 'rb')) ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.