将私人数据导入谷歌协作笔记本的常用方法是什么?是否可以导入一个非公开的谷歌表?不能从系统文件中读取。介绍性文档链接到使用BigQuery的指南，但这似乎有点…多。
当前回答
如果数据集大小小于25mb，最简单的方法是从你的GitHub存储库上传CSV文件。
单击存储库中的数据集 点击“查看原始”按钮 复制链接并将其存储在一个变量中 将变量加载到Pandas read_csv中以获得数据帧
例子:
import pandas as pd
url = 'copied_raw_data_link'
df1 = pd.read_csv(url)
df1.head()
其他回答
对于那些像我一样从谷歌搜索关键字“上传文件colab”的人:
from google.colab import files
uploaded = files.upload()
快速，简单地从Dropbox导入:
!pip install dropbox
import dropbox
access_token = 'YOUR_ACCESS_TOKEN_HERE' # https://www.dropbox.com/developers/apps
dbx = dropbox.Dropbox(access_token)
# response = dbx.files_list_folder("")
metadata, res = dbx.files_download('/dataframe.pickle2')
with open('dataframe.pickle2', "wb") as f:
f.write(res.content)
正如@Vivek Solanki所提到的，我也在协作仪表板的“文件”部分上传了我的文件。 只需要注意文件上传的位置。对我来说, train_data = pd.read_csv('/fileName.csv')有效。
如果数据集大小小于25mb，最简单的方法是从你的GitHub存储库上传CSV文件。
单击存储库中的数据集 点击“查看原始”按钮 复制链接并将其存储在一个变量中 将变量加载到Pandas read_csv中以获得数据帧
例子:
import pandas as pd
url = 'copied_raw_data_link'
df1 = pd.read_csv(url)
df1.head()
已解决，请在这里找到详细信息，并使用下面的功能: https://stackoverflow.com/questions/47212852/how-to-import-and-read-a-shelve-or-numpy-file-in-google-colaboratory/49467113#49467113
from google.colab import files
import zipfile, io, os
def read_dir_file(case_f):
# author: yasser mustafa, 21 March 2018
# case_f = 0 for uploading one File and case_f = 1 for uploading one Zipped Directory
uploaded = files.upload() # to upload a Full Directory, please Zip it first (use WinZip)
for fn in uploaded.keys():
name = fn #.encode('utf-8')
#print('\nfile after encode', name)
#name = io.BytesIO(uploaded[name])
if case_f == 0: # case of uploading 'One File only'
print('\n file name: ', name)
return name
else: # case of uploading a directory and its subdirectories and files
zfile = zipfile.ZipFile(name, 'r') # unzip the directory
zfile.extractall()
for d in zfile.namelist(): # d = directory
print('\n main directory name: ', d)
return d
print('Done!')
