Question

我有一个包含3列的CSV文件：

第1列-总值-是 ID_IP地址的链接 [51515151 99.999.999.999]
第2列-时间列-时间 [2019-02-25T19：04：59.999-0500]
第3列- IP地址（IPv4和IPv6 ）- IP [99.999.999.999]

我试图通过将第一列中的ID分为两列来解析ID和IP地址，然后丢弃具有新创建的IP地址的列，因为它们已经包含在第3列中了。

这是我到目前为止的代码：

import pandas as pd
from pandas import read_csv
df1= pd.read_csv('C:\\Users\\[redacted]\\Documents\\Python\\Parsing.csv')
df1.dropna(inplace = True) # dropping null value columns to avoid errors
df1 = df1["Overall Value"].str.split(" ", n = 1, expand = True) # updating data frame with split value columns
df1["ID"]= df1[0] # making seperate ID column from new data frame
df1["IP2"]= df1[1] # making seperate IP column from new data frame
df1["Time"]= df1[2]
df1["IP"]= df1[3]
df1.drop(columns =["IP2"], inplace = True) # deleting column 2
df2 = pd.read_csv('C:\\Users\\[redacted]\\Documents\\Python\\Parsingcopy.csv', index_col=0)
df1 = df1.map(df2)
df1.to_csv('C:\\Users\\[redacted]\\Documents\\Python\\Parsingcopy2.csv')

为什么会给我以下错误？

C:\Users\[Redacted]>C:\Python27\python.exe C:\Users\[Redacted]\Documents\Python\Parsing.py
Traceback (most recent call last):
File "C:\Users\[Redacted]\Documents\Python\Parsing.py", line 21, in <module>
    df1["RestofData"]= df1[2]
  File "C:\Python27\lib\site-packages\pandas\core\frame.py", line 2139, in __getitem__
    return self._getitem_column(key)
  File "C:\Python27\lib\site-packages\pandas\core\frame.py", line 2146, in _getitem_column
    return self._get_item_cache(key)
  File "C:\Python27\lib\site-packages\pandas\core\generic.py", line 1842, in _get_item_cache
    values = self._data.get(item)
  File "C:\Python27\lib\site-packages\pandas\core\internals.py", line 3843, in get
    loc = self.items.get_loc(item)
  File "C:\Python27\lib\site-packages\pandas\core\indexes\base.py", line 2527, in get_loc
    return self._engine.get_loc(self._maybe_cast_indexer(key))
  File "pandas\_libs\index.pyx", line 117, in pandas._libs.index.IndexEngine.get_loc
  File "pandas\_libs\index.pyx", line 139, in pandas._libs.index.IndexEngine.get_loc
  File "pandas\_libs\hashtable_class_helper.pxi", line 1265, in pandas._libs.hashtable.PyObjectHashTable.get_item
  File "pandas\_libs\hashtable_class_helper.pxi", line 1273, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: 2

Answer 1

这样做：

df1 = df1["Overall Value"].str.split(...)

您不是更新现有数据框，而是创建一个新数据框并将其指向df1名称。

df1现在不再引用原始数据帧，因此df[2]告诉您的是df[3]（和KeyError: 2）不存在。

相反，您应该对临时数据框使用其他名称，然后使用该名称更新原始数据框中的列。

此外，与其先创建两个新列，而不仅仅是立即丢弃其中一列，不如仅使用实际需要的列。

对于已经存在的其余列，应该使用索引1和2而不是2和3，但是由于它们已经包含在df1中，因此不必“重新插入”它们。 / p>

类似这样的东西：

ids_ips = df1["Overall Value"].str.split(" ", n = 1, expand = True)
df1["ID"] = ids_ips[0]
# df1["IP2"] = ids_ips[1]  <-- don't do this
df1["Time"] = df1[1]  # this is probably not necessary, too
df1["IP"] = df1[2]    # neither is this

解析，删除和屏蔽IP地址的脚本

1 个答案: