读取csv文件，解析数据，存入字典

Question

我有一个文件，其中包含电台最近播放的歌曲、艺术家和播放时间，格式如下："November 4, 2019 8:02 PM"、"Wagon Wheel"、"Darius Rucker"。我试图将此文件的内容存储在字符串变量 playlist_csv 中，使用 splitlines() 将记录存储在可变行中，然后遍历这些行以将数据存储在字典中。键应该是时间戳的日期时间对象，值应该是歌曲和艺术家的元组：{datetime_key: (song, artist)}

文件摘录如下：

"November 4, 2019 8:02 PM","Wagon Wheel","Darius Rucker" 
"November 4, 2019 7:59 PM","Remember You Young","Thomas Rhett" 
"November 4, 2019 7:55 PM","Long Hot Summer","Keith Urban"

所需词典应如下所示：

{datetime.datetime(2019, 11, 4, 20, 2): ('Wagon Wheel', 'Darius Rucker'), 
datetime.datetime(2019, 11, 4, 19, 59): ('Remember You Young', 'Thomas Rhett'), 
datetime.datetime(2019, 11, 4, 19, 55): ('Long Hot Summer', 'Keith Urban')}

这是我到目前为止的代码：

# read the file and store content in string variable playlist_csv
with open('playlist.txt', 'r') as csv_file:
    playlist_csv = csv_file.read().replace('\n', '')
    # use splitlines() method to store records in variable lines (it is list)
    split_playlist = playlist_csv.splitlines()
    # iterate through lines to store data in playlist_dict dictionary
    playlist_dict = {}
    for l in csv.reader(split_playlist, quotechar='"', delimiter=',',
       quoting=csv.QUOTE_ALL, skipinitialspace=True):
       dt=datetime.strptime(l[0], '%B %d, %Y %I:%M %p')
       playlist_dict[l[dt]].append(dt)
print(playlist_dict)

但是，当我尝试将此数据存储在字典中时，我一直运行出错（特别是“'datetime.datetime' 对象不可订阅”和 "list indices must be integers or slices" 修改代码时）。

感谢任何帮助！

Answer 1

您首先尝试拆分 csv 文件似乎是不必要的 - csv.reader 会为您处理所有这些。而不是 playlist_dict[l[dt]].append(dt) 你需要像 playlist_dict[dt].append((song, artist)) 这样的东西。这应该有效：

with open('playlist.txt', 'r') as csv_file:
    playlist = {}
    for time, song, artist in csv.reader(csv_file):
        time = datetime.strptime(time, '%B %d, %Y %I:%M %p')
        if time in playlist:
            playlist[time].append((song, artist))
        else:
            playlist[time] = [(song, artist)]

（您提供给 csv.reader 的可选参数可能也不需要 - 默认值应该适用于您提供的输入类型。）

或者如果你在每个日期时间只有一个可能的 song/artist 那么你不需要一个列表并且可以这样做（这似乎是你正在寻找的输出）：

with open('playlist.txt', 'r') as f:
    playlist = {datetime.strptime(time, '%B %d, %Y %I:%M %p'): (song, artist) 
                for time, song, artist in csv.reader(f)}

Answer 2

事实证明，对于这种情况它可能是更好的选择，这里是使用 Pandas 的解决方案。作为奖励，它计算每首歌曲之间的时间。

import pandas as pd

df = pd.read_csv('../resources/radio_songs.csv', dtype={'song_name': str, 'artist': str},
                 parse_dates=[0], header=None, names=['time_played', 'song_name', 'artist'])

df['time_diff'] = df['time_played'].diff(periods=-1)

DataFrame 输出：

          time_played           song_name         artist time_diff
0 2019-11-04 20:02:00         Wagon Wheel  Darius Rucker  00:03:00
1 2019-11-04 19:59:00  Remember You Young   Thomas Rhett  00:04:00
2 2019-11-04 19:55:00     Long Hot Summer    Keith Urban       NaT

如果出于某种原因您需要它，可以通过以下有趣的方式重新创建该字典格式：

tuples_dict = dict(zip(df['time_played'], zip(df['song_name'], df['artist'])))

输出：

{Timestamp('2019-11-04 20:02:00'): ('Wagon Wheel', 'Darius Rucker'), Timestamp('2019-11-04 19:59:00'): ('Remember You Young', 'Thomas Rhett'), Timestamp('2019-11-04 19:55:00'): ('Long Hot Summer', 'Keith Urban')}

读取csv文件，解析数据，存入字典

Read csv file, parse data, and store in a dictionary

python

dictionary

python-3.6