小编Cos*_*oCD的帖子

我需要比较两个列表,以便创建一个列表中找到的特定元素的新列表,但不能在另一个列表中找到.例如:

main_list=[]
list_1=["a", "b", "c", "d", "e"]
list_2=["a", "f", "c", "m"] 

我想循环遍历list_1并向list_list追加list_2中找不到的所有元素.

结果应该是:

main_list=["f", "m"]

我怎么能用python做到这一点？

我有一个dict列表,如下所示:

list=[{u'hello':['001', 3], u'word':['003', 1], u'boy':['002', 2]}, 
     {u'dad':['007', 3], u'mom':['005', 3], u'honey':['002', 2]} ] 

我需要的是迭代我的列表,以创建这样的元组列表:

new_list=[('hello','001', 3), ('word','003',1), ('boy','002', 2)
           ('dad','007',3), ('mom', '005', 3), ('honey','002',2)]

注意!零('001',003'等等)的数字必须考虑为字符串.

有没有人可以帮助我？

我正在 python3 环境中使用 pyspark。我有一个数据框，我正在尝试将一列密集 vectos 拆分为多个列值。我的 df 是这样的：

df_vector = kmeansModel_2.transform(finalData).select(['scalaredFeatures', 
                                                       'prediction'])
df_vector.show()

+--------------------+----------+
|    scalaredFeatures|prediction|
+--------------------+----------+
|[0.56785108466505...|         0|
|[1.41962771166263...|         0|
|[2.20042295307707...|         0|
|[0.14196277116626...|         0|
|[1.41962771166263...|         0|
+-------------------------------+

好吧，为了完成我的任务，我使用了以下代码：

def extract(row):
    return (row.prediction, ) + tuple(row.scalaredFeatures.toArray().tolist())

df = df_vector.rdd.map(extract)toDF(["prediction"])

不幸的是，我收到一个错误：

Py4JJavaError: An error occurred while calling 
z:org.apache.spark.api.python.PythonRDD.runJob.
: org.apache.spark.SparkException: Job aborted due to stage failure: 
Task 0 in stage 52.0 failed 1 times, most recent failure: Lost task 
0.0 in stage 52.0 (TID 434, localhost, executor driver): 
org.apache.spark.api.python.PythonException: Traceback (most …

在网络抓取电子商务网站后,我已将所有数据保存到pandas数据框中.好吧,当我试图将我的pandas数据帧保存到excel文件但是我收到以下错误:

Traceback (most recent call last):

File "<ipython-input-7-3dafdf6b87bd>", line 2, in <module>
  sheet_name='Dolci', encoding='iso-8859-1')

File "C:\ProgramData\Anaconda2\lib\site-packages\pandas\core\frame.py", line 
  1466, in to_excel
     excel_writer.save()

File "C:\ProgramData\Anaconda2\lib\site-packages\pandas\io\excel.py", line 
  1502, in save
     return self.book.close()

File "C:\ProgramData\Anaconda2\lib\site-packages\xlsxwriter\workbook.py", 
  line 299, in close
     self._store_workbook()

File "C:\ProgramData\Anaconda2\lib\site-packages\xlsxwriter\workbook.py", 
  line 607, in _store_workbook
     xml_files = packager._create_package()

File "C:\ProgramData\Anaconda2\lib\site-packages\xlsxwriter\packager.py", 
  line 139, in _create_package
     self._write_shared_strings_file()

File "C:\ProgramData\Anaconda2\lib\site-packages\xlsxwriter\packager.py", 
  line 286, in _write_shared_strings_file
     sst._assemble_xml_file()

File "C:\ProgramData\Anaconda2\lib\site-
  packages\xlsxwriter\sharedstrings.py", line 53, in _assemble_xml_file
     self._write_sst_strings()

File "C:\ProgramData\Anaconda2\lib\site-
  packages\xlsxwriter\sharedstrings.py", line 83, in _write_sst_strings
     self._write_si(string)

File "C:\ProgramData\Anaconda2\lib\site-
  packages\xlsxwriter\sharedstrings.py", line 110, …