英文:
problem trying to read a csv file but the extension does not appear
问题
我正在尝试打开来自Spotify数据库的CSV文件，以处理其Sequential Skip Predictions数据集。但是，它的列和行存在一些问题，我无法弄清楚如何修复。我最多只能打开表格，忽略一些问题，但仍然存在很多错误。
链接如下：
我试图访问的文件是：
Training_Set_And_Track_Features_Mini（17.2 MB）
我使用了以下代码，这是我设法打开它的内容：
import pandas as pd
# CSV文件路径
path_file = '/content/drive/MyDrive/TESTE TCC/training mini/16772e7f-7871-4d42-a44f-5f399f40fd94_training_set_track_features_mini'
# 打开CSV
data = pd.read_csv(file_path, encoding='latin1', error_bad_lines=False)
# 显示数据
data
但即便如此，它仍然存在许多错误，列也都很奇怪。
英文:
Well, I'm trying to open a CSV file from the Spotify Database, to work with its Sequential Skip Predictions dataset. But he has some problem with his columns and rows that I can't figure out how to fix. The most I could do was open the table ignoring some problems but it still gets very buggy.
The link is this:
Link for Spotify Sequential Skip Prediction Challange
The file I'm trying to access is this:
Training_Set_And_Track_Features_Mini (17.2 MB)
I used this code here, which is what I managed to do to open it:
import pandas as pd
# path csv
path_file = '/content/drive/MyDrive/TESTE TCC/training mini/16772e7f-7871-4d42-a44f-5f399f40fd94_training_set_track_features_mini'
# Open CSV
data = pd.read_csv(file_path, encoding='latin1', error_bad_lines=False)
# display the data
data
but even so, it's still very buggy, and the columns are all weird
答案1
得分: 2
这是一个tar.gz档案，在使用之前需要解压缩：
为此，请运行以下Shell命令：
tar -xzf 16772e7f-7871-4d42-a44f-5f399f40fd94_training_set_track_features_mini.tar.tar
这将创建一个包含CSV文件的data文件夹。
然后，从您的Python脚本/笔记本中执行以下操作：
df_features = pd.read_csv('data/track_features/tf_mini.csv')
df_train = pd.read_csv('data/training_set/log_mini.csv')
英文:
This is a tar.gz archive, which you need to extract before using:
For this, run this shell command:
tar -xzf 16772e7f-7871-4d42-a44f-5f399f40fd94_training_set_track_features_mini.tar.tar
This will create a data folder that contains the CSV files.
Then, from your python script/notebook:
df_features = pd.read_csv('data/track_features/tf_mini.csv')
df_train = pd.read_csv('data/training_set/log_mini.csv')
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