从下载url导入Kaggle csv到熊猫DataFrame

问题描述:

我一直在尝试使用不同的方法将SpaceX任务csv fileKaggle直接导入到熊猫DataFrame中,但没有任何成功。从下载url导入Kaggle csv到熊猫DataFrame

我需要发送请求登录。这是我到目前为止:

import requests 
import pandas as pd 
from io import StringIO 

# Link to the Kaggle data set & name of zip file 
login_url = 'http://www.kaggle.com/account/login?ReturnUrl=/spacex/spacex-missions/downloads/database.csv' 

# Kaggle Username and Password 
kaggle_info = {'UserName': "user", 'Password': "pwd"} 

# Login to Kaggle and retrieve the data. 
r = requests.post(login_url, data=kaggle_info, stream=True) 
df = pd.read_csv(StringIO(r.text)) 

r正在返回页面的html内容。 df = pd.read_csv(url)给出了CParser错误: CParserError: Error tokenizing data. C error: Expected 1 fields in line 13, saw 6

我搜索了一个解决方案,但到目前为止,没有我试着努力。

您正在创建一个流并将其直接传递给熊猫。我认为你需要传递一个像熊猫一样的文件。看看this answer寻找一个可能的解决方案(使用帖子,而不是在请求中)。

此外,我认为您使用的重定向登录网址不能正常工作。 I know i suggested that here。但我最终没有使用是因为后请求调用没有处理重定向(我怀疑)。

最后我用我的项目中的代码是这样的:

def from_kaggle(data_sets, competition): 
    """Fetches data from Kaggle 

    Parameters 
    ---------- 
    data_sets : (array) 
     list of dataset filenames on kaggle. (e.g. train.csv.zip) 

    competition : (string) 
     name of kaggle competition as it appears in url 
     (e.g. 'rossmann-store-sales') 

    """ 
    kaggle_dataset_url = "https://www.kaggle.com/c/{}/download/".format(competition) 

    KAGGLE_INFO = {'UserName': config.kaggle_username, 
        'Password': config.kaggle_password} 

    for data_set in data_sets: 
     data_url = path.join(kaggle_dataset_url, data_set) 
     data_output = path.join(config.raw_data_dir, data_set) 
     # Attempts to download the CSV file. Gets rejected because we are not logged in. 
     r = requests.get(data_url) 
     # Login to Kaggle and retrieve the data. 
     r = requests.post(r.url, data=KAGGLE_INFO, stream=True) 
     # Writes the data to a local file one chunk at a time. 
     with open(data_output, 'wb') as f: 
      # Reads 512KB at a time into memory 
      for chunk in r.iter_content(chunk_size=(512 * 1024)): 
       if chunk: # filter out keep-alive new chunks 
        f.write(chunk) 

使用例:

sets = ['train.csv.zip', 
     'test.csv.zip', 
     'store.csv.zip', 
     'sample_submission.csv.zip',] 
from_kaggle(sets, 'rossmann-store-sales') 

您可能需要解压缩文件。

def _unzip_folder(destination): 
    """Unzip without regards to the folder structure. 

    Parameters 
    ---------- 
    destination : (str) 
     Local path and filename where file is should be stored. 
    """ 
    with zipfile.ZipFile(destination, "r") as z: 
     z.extractall(config.raw_data_dir) 

所以我从来没有真正直接装载入数据帧,而是将其存储到磁盘第一。但是,您可以修改它以使用临时目录,并在读取它们后删除这些文件。

+0

我想大熊猫可以在ziped时读取csv文件。 http://*.com/questions/18885175/read-a-zipped-file-as-a-pandas-dataframe –