Question

我要下载许多.csv文件，这些文件会转换为pandas数据帧并相互附加。

可以通过每天创建的url来访问csv，并且可以使用datetime轻松地将其生成并放在列表中。

我可以在列表中单独打开它们。

当我尝试打开其中一些并将它们附加在一起时，我得到一个空的数据框。代码看起来像这样。

#Imports
import datetime 
import pandas as pd


#Testing can open .csv file
data = pd.read_csv('https://promo.betfair.com/betfairsp/prices/dwbfpricesukwin01022018.csv')
data.iloc[:5]


#Taking heading to use to create new dataframe 
data_headings = list(data.columns.values)


#Setting up string for url
path_start = 'https://promo.betfair.com/betfairsp/prices/dwbfpricesukwin'
file = ".csv"


#Getting dates which are used in url 
start = datetime.datetime.strptime("01-02-2018", "%d-%m-%Y")
end = datetime.datetime.strptime("04-02-2018", "%d-%m-%Y")
date_generated = [start + datetime.timedelta(days=x) for x in range(0, (end-start).days)]


#Creating new dataframe which is appended to
for heading in data_headings:
    data = {heading: []}

df = pd.DataFrame(data, columns=data_headings)


#Creating list of url
date_list = []

for date in date_generated:
    date_string = date.strftime("%d%m%Y")

    x = path_start + date_string + file
    date_list.append(x)


#Opening and appending csv files from list which contains url
for full_path in date_list:
    data_link = pd.read_csv(full_path)
    df.append(data_link)

print(df)

我已经检查了它们不仅是空的csv，而且不是。任何帮助将不胜感激。

干杯，桑迪

Answer 1

您永远不会存储附加的数据帧。该行：

df.append(data_link)

应该是

df = df.append(data_link)

但是，这可能是错误的方法。您确实想使用URL数组并将它们连接起来。查看this similar question，看看它是否可以改善您的代码！

Answer 2

我真的不明白你想在这里做什么：

#Creating new dataframe which is appended to
for heading in data_headings:
    data = {heading: []}

df = pd.DataFrame(data, columns=data_headings)

顺便尝试一下：

for full_path in date_list:
    data_link = pd.read_csv(full_path)
    df.append(data_link.copy())

使用for循环附加多个熊猫数据框，但返回一个空数据框

2 个答案: