在 Python 2.7 (Pandas 0.22.0) 中,将 Pandas 数据帧保存到内存中的 gzipped csv 的工作方式如下:
from io import BytesIO
import gzip
import pandas as pd
df = pd.DataFrame.from_dict({'a': ['a', 'b', 'c']})
s = BytesIO()
f = gzip.GzipFile(fileobj=s, mode='wb', filename='file.csv')
df.to_csv(f)
s.seek(0)
content = s.getvalue()
Run Code Online (Sandbox Code Playgroud)
但是,在 Python 3.6 (Pandas 0.22.0) 中,相同的代码在调用时会抛出错误to_csv:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "lib/python3.6/site-packages/pandas/core/frame.py", line 1524, in to_csv
formatter.save()
File "lib/python3.6/site-packages/pandas/io/formats/format.py", line 1652, in save
self._save()
File "lib/python3.6/site-packages/pandas/io/formats/format.py", line 1740, in _save
self._save_header()
File "lib/python3.6/site-packages/pandas/io/formats/format.py", line 1708, in _save_header
writer.writerow(encoded_labels)
File "miniconda3/lib/python3.6/gzip.py", line 260, in write
data = memoryview(data)
TypeError: memoryview: a bytes-like object is required, not 'str'
Run Code Online (Sandbox Code Playgroud)
我应该如何解决这个问题?我是否需要以GzipFile某种方式更改对象以to_csv正确处理它?
为了澄清起见,我想在内存中创建 gzip 压缩文件(content变量),以便稍后使用Boto 3put_object将其保存到 Amazon S3 。
您可以利用StringIO:
from io import StringIO
buf = StringIO()
df.to_csv(buf)
f = gzip.GzipFile(fileobj=s, mode='wb', filename='file.csv')
f.write(buf.getvalue().encode())
f.flush()
Run Code Online (Sandbox Code Playgroud)
另请注意添加的f.flush()- 根据我的经验,如果没有这条线,GzipFile在某些情况下可能会随机不刷新数据,从而导致存档损坏。
或者作为基于您的代码的完整示例:
from io import BytesIO
import gzip
import pandas as pd
from io import StringIO
df = pd.DataFrame.from_dict({'a': ['a', 'b', 'c']})
s = BytesIO()
buf = StringIO()
f = gzip.GzipFile(fileobj=s, mode='wb', filename='file.csv')
df.to_csv(buf)
f.write(buf.getvalue().encode())
f.flush()
s.seek(0)
content = s.getvalue()
Run Code Online (Sandbox Code Playgroud)