如何在PySpark中使用read.csv跳过多行 [英] How to skip multiple lines using read.csv in PySpark
问题描述
我的.csv
列很少,并且在使用spark.read.csv()
函数将此文件导入数据帧时,希望跳过4(或通常为'n'
)行.我有这样的.csv
文件-
I am having a .csv
with few columns, and I wish to skip 4 (or 'n'
in general) lines when importing this file into a dataframe using spark.read.csv()
function. I have a .csv
file like this -
ID;Name;Revenue
Identifier;Customer Name;Euros
cust_ID;cust_name;€
ID132;XYZ Ltd;2825
ID150;ABC Ltd;1849
在普通的Python中,使用read_csv()
函数时,它很简单,并且可以使用skiprow=n
选项(例如-
In normal Python, when using read_csv()
function, it's simple and can be done using skiprow=n
option like -
import pandas as pd
df=pd.read_csv('filename.csv',sep=';',skiprows=3) # Since we wish to skip top 3 lines
使用PySpark,我可以按如下方式导入此.csv文件-
With PySpark, I am importing this .csv file as follows -
df=spark.read.csv("filename.csv",sep=';')
This imports the file as -
ID |Name |Revenue
Identifier |Customer Name|Euros
cust_ID |cust_name |€
ID132 |XYZ Ltd |2825
ID150 |ABC Ltd 1849
这是不正确的,因为我希望忽略前三行.我不能使用选项'header=True'
,因为它只会排除第一行.可以使用'comment='
选项,但为此需要以特殊字符开头的行,而我的文件则不是这样.我在文档中找不到任何内容.有什么办法可以实现?
This is not correct, because I wish to ignore first three lines. I can't use option 'header=True'
because it will only exclude the first line. One can use 'comment='
option, but for that one needs the lines to start with a particular character and that is not the case with my file. I could not find anything in the documentation. Is there any way this can be accomplished?
推荐答案
我找不到适合您问题的简单解决方案.尽管无论标头如何写入都可以这样做,
I couldnt find a simple solution for your problem. Although this will work no matter how the header is written,
df = spark.read.csv("filename.csv",sep=';')\
.rdd.zipWithIndex()\
.filter(lambda x: x[1] > n)\
.map(lambda x: x[0]).toDF()
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