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
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!')
其他回答
步骤1-挂载您的谷歌驱动器到协作实验室
from google.colab import drive
drive.mount('/content/gdrive')
第2步-现在你会看到你的谷歌驱动器文件在左侧窗格(文件资源管理器)。右键单击需要导入的文件并选择çopy路径。 然后像往常一样在pandas中导入,使用这个复制的路径。
import pandas as pd
df=pd.read_csv('gdrive/My Drive/data.csv')
完成了!
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!')
到目前为止,我发现的最简单的解决方案,适用于中小型CSV文件是:
在gi.github.com上创建一个秘密要点,然后上传(或复制粘贴)你的文件。 单击Raw视图并复制原始文件URL。 在调用pandas.read_csv(URL)时,使用复制的URL作为文件地址
这对于逐行读取文本文件或二进制文件可能有效,也可能无效。
我创建了一小段代码,可以以多种方式实现这一点。你可以
使用已经上传的文件(在重新启动内核时很有用) 使用来自Github的文件 手动上传文件
import os.path
filename = "your_file_name.csv"
if os.path.isfile(filename):
print("File already exists. Will reuse the same ...")
else:
use_github_data = False # Set this to True if you want to download from Github
if use_github_data:
print("Loading fie from Github ...")
# Change the link below to the file on the repo
filename = "https://github.com/ngupta23/repo_name/blob/master/your_file_name.csv"
else:
print("Please upload your file to Colab ...")
from google.colab import files
uploaded = files.upload()
从谷歌。Colab导入驱动器
驱动器(' /内容/ drive’山)
进口熊猫作为pd dv = pd.read_csv(' /内容/传动/ MyDrive /戴安娜/卡索/ Data_Caso_Propuesto.csv”) dv.info ()