lot*_*man 4 python csv pandas python-requests
我想从带有请求的链接下载csv文件并将其另存为MSFT.csv.但是,我的代码返回错误
文件"<stdin>",第1行,在_csv.Error中:在未引用字段中看到的新行字符 - 您是否需要以通用换行模式打开文件?
import requests
import csv
data=requests.get('https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol=MSFT&apikey=demo&datatype=csv'
cr = csv.reader(data)
for row in cr:
print row
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我怎么能用它保存MSFT.csv?
cs9*_*s95 10
如果您尝试将此数据写入CSV文件,可以先使用下载requests.get.
import csv
import requests
url = 'https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol=MSFT&apikey=demo&datatype=csv'
response = requests.get(url)
with open('out.csv', 'w') as f:
writer = csv.writer(f)
for line in response.iter_lines():
writer.writerow(line.decode('utf-8').split(','))
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如果您正在使用pip install --user pandas,则将requests.get内容传递给pip install --user pandas并迭代:
import pandas as pd
df = pd.read_csv(url)
df.head()
timestamp open high low close adjusted_close volume dividend_amount split_coefficient
0 2019-06-19 135.00 135.93 133.81 135.69 135.69 17946556 0.0 1.0
1 2019-06-18 134.19 135.24 133.57 135.16 135.16 25908534 0.0 1.0
2 2019-06-17 132.63 133.73 132.53 132.85 132.85 14517785 0.0 1.0
3 2019-06-14 132.26 133.79 131.64 132.45 132.45 17821703 0.0 1.0
4 2019-06-13 131.98 132.67 131.56 132.32 132.32 17200848 0.0 1.0
df.to_csv('out.csv')
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或者,使用pandas,发送requests.get到缓冲区并传递给它pip install --user pandas.
import csv
import requests
url = 'https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol=MSFT&apikey=demo&datatype=csv'
response = requests.get(url)
with open('out.csv', 'w') as f:
writer = csv.writer(f)
for line in response.iter_lines():
writer.writerow(line.decode('utf-8').split(','))
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您可以通过请求实现它
import os
import requests
def download_file(url, filename):
''' Downloads file from the url and save it as filename '''
# check if file already exists
if not os.path.isfile(filename):
print('Downloading File')
response = requests.get(url)
# Check if the response is ok (200)
if response.status_code == 200:
# Open file and write the content
with open(filename, 'wb') as file:
# A chunk of 128 bytes
for chunk in response:
file.write(chunk)
else:
print('File exists')
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您可以使用所需的 url 和文件名调用该函数。在您的情况下,它将是:
url = 'https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol=MSFT&apikey=demo&datatype=csv'
filename = 'MSFT.csv'
download_file(url, filename)
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希望这可以帮助。
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