导入csv到pandas数据框时未读取所有行 [英] Not reading all rows while importing csv into pandas dataframe

问题描述

我正在尝试此处，并且很不幸，一个非常基本的步骤.我的有限的python知识必须为此负责. 我正在尝试通过执行以下命令，将数据集读取到熊猫数据框中. :

I am trying the kaggle challenge here, and unfortunately I am stuck at a very basic step. My limited python knowledge has to be blamed for this. I am trying to read the datasets into a pandas dataframe by executing following command:

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

问题在于，您将发现该文件具有超过300,000条记录，但我只读取了7945，21.

The problem is that this file as you would find out has over 300,000 records, but I am reading only 7945, 21.

print (test.shape)
(7945, 21)

现在，我已经仔细检查了文件，但找不到关于行号7945的特殊信息.任何可能导致这种情况的指针.看来情况很普通，我希望遇到这个错误的一些人能帮助我.

Now I have double checked the file and I cannot find anything special about line number 7945. Any pointers why this could be happening. Seems very ordinary situation, I hope some of you who have ran across this error can help me out.

推荐答案

我认为更好的方法是使用函数链接

I think better is use function 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.

But some data (problematic) will be skipped.

如果要跳过电子邮件正文数据，可以使用:

If you want skip emails body data, you can use:

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']

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