在Python 2.7(Pandas 0.22.0)中,将Pandas数据框保存为内存中的gzipped csv格式可以按以下方式完成:
我该如何解决这个问题?我需要在
澄清一下,我想在内存中创建压缩文件(即
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()
然而在 Python 3.6 (Pandas 0.22.0) 中,调用 to_csv
会抛出错误:
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'
我该如何解决这个问题?我需要在
to_csv
正确处理它之前改变GzipFile
对象吗?澄清一下,我想在内存中创建压缩文件(即
content
变量),以便稍后使用Boto 3 put_object
将其保存到Amazon S3。