将多个元素插入存在相似之处的熊猫系列中

Question

在这里，我想在标签中插入两个行带有" href"的任何地方之间的行 "<td class='test'>None</td>"-注意，带有href的每行都不相同。

import pandas as pd
table = pd.Series(
        ["<td class='test'><a class='test' href=...", # 0 
        "<td class='test'>A</td>",                    # 1
        "<td class='test'><a class='test' href=...",  # 2
        "<td class='test'>B</td>",                    # 3
        "<td class='test'><a class='test' href=...",  # 4
        "<td class='test'><a class='test' href=...",  # 5
        "<td class='test'>C</td>",                    # 6
        "<td class='test'><a class='test' href=...",  # 7 
        "<td class='test'>F</td>",                    # 8
        "<td class='test'><a class='test' href=...",  # 9 
        "<td class='test'><a class='test' href=...",  # 10 
        "<td class='test'>X</td>"])                   # 11
insertAt = []
for i in range(0, len(table)):
  if 'href' in table[i] and 'href' in table[i+1]:
    print(i + 1, ' is duplicated')
    insertAt.append(i)
# 5  is duplicated
# 10  is duplicated
# [4, 9]

这是输出应该看起来的：

#         ["<td class='test'><a class='test' href=...", # 0 
#         "<td class='test'>A</td>",                    # 1
#         "<td class='test'><a class='test' href=...",  # 2
#         "<td class='test'>B</td>",                    # 3
#         "<td class='test'><a class='test' href=...",  # 4
#         "<td class='test'>None</td>",                 # 5 Insert "<td class='test'>None</td>"
#         "<td class='test'><a class='test' href=...",  # 6
#         "<td class='test'>C</td>",                    # 7
#         "<td class='test'><a class='test' href=...",  # 8 
#         "<td class='test'>F</td>",                    # 9
#         "<td class='test'><a class='test' href=...",  # 10
#         "<td class='test'>None</td>",                 # 11 Insert <td class='test'>None</td>"
#         "<td class='test'><a class='test' href=...",  # 12 
#         "<td class='test'>X</td>"]                    # 13

Answer 1

如果您转到numpy，可以轻松实现。

在您的示例中：

dups = table.str.contains('href') & table.shift(1).str.contains('href')
array = np.insert(table.values, dups[dups].index, "<td class='test'>None</td>")
pd.Series(array)

Answer 2

ecotrazar上面的解决方案既更快又优雅。这是我的版本用于循环和他的numpy插入方法。

import pandas as pd
table = pd.Series(
        ["<td class='test'><a class='test' href=...", # 0 
        "<td class='test'>A</td>",                    # 1
        "<td class='test'><a class='test' href=...",  # 2
        "<td class='test'>B</td>",                    # 3
        "<td class='test'><a class='test' href=...",  # 4
        "<td class='test'><a class='test' href=...",  # 5
        "<td class='test'>C</td>",                    # 6
        "<td class='test'><a class='test' href=...",  # 7 
        "<td class='test'>F</td>",                    # 8
        "<td class='test'><a class='test' href=...",  # 9 
        "<td class='test'><a class='test' href=...",  # 10 
        "<td class='test'>X</td>"])                   # 11
insertAt = []
for i in range(0, len(table)):
  if 'href' in table[i] and 'href' in table[i + 1] and i == 0:
    print(i + 1, ' is duplicated')
    insertAt.append(True)
  elif i == 0:
     insertAt.append(False)
  if 'href' in table[i] and 'href' in table[i+1] and i > 0:
    print(i + 1, ' is duplicated')
    insertAt.append(True)
  else:
    insertAt.append(False)
insertAt = pd.Series(insertAt)
print(insertAt)
import numpy as np
array = np.insert(table.values, insertAt[insertAt].index, "<td class='test'>None</td>")
pd.Series(array) # back to series if necessary