将 csv 导入 pandas 数据框时不读取所有行

Question

我正在尝试 kaggle 挑战 here，不幸的是，我卡在了一个非常基本的步骤。这都怪我 python 知识有限。我正在尝试通过执行以下命令将 datasets 读入 pandas 数据帧：

test = pd.DataFrame.from_csv("C:/Name/DataMining/hillary/data/output/emails.csv")

问题是你会发现这个文件有超过 300,000 条记录，但我只读取 7945、21。

print (test.shape)
(7945, 21)

现在我已经仔细检查了文件，但我找不到关于行号 7945 的任何特殊之处。任何可能发生这种情况的指针。看起来很普通的情况，希望有运行遇到这个错误的朋友能帮帮我。

Answer 1

我认为使用函数更好 read_csv with parameters quoting=csv.QUOTE_NONE and error_bad_lines=False. link

import pandas as pd
import csv

test = pd.read_csv("output/Emails.csv", quoting=csv.QUOTE_NONE, error_bad_lines=False)

print (test.shape)
#(381422, 22)

但是一些数据（有问题的）将被跳过。

如果你想跳过邮件正文数据，你可以使用：

import pandas as pd
import csv

test = pd.read_csv("output/Emails.csv", quoting=csv.QUOTE_NONE,  sep=',', error_bad_lines=False, header=None,
    names=["Id","DocNumber","MetadataSubject","MetadataTo","MetadataFrom","SenderPersonId","MetadataDateSent","MetadataDateReleased","MetadataPdfLink","MetadataCaseNumber","MetadataDocumentClass","ExtractedSubject","ExtractedTo","ExtractedFrom","ExtractedCc","ExtractedDateSent","ExtractedCaseNumber","ExtractedDocNumber","ExtractedDateReleased","ExtractedReleaseInPartOrFull","ExtractedBodyText","RawText"])

print (test.shape)

#delete row with NaN in column MetadataFrom
test = test.dropna(subset=['MetadataFrom'])
#delete headers in data
test = test[test.MetadataFrom != 'MetadataFrom']

将 csv 导入 pandas 数据框时不读取所有行

Not reading all rows while importing csv into pandas dataframe

python-3.x

csv

pandas

machine-learning

kaggle