Question

我有一个这样的数据框：

value1       value2
aa7bbc       aaaa
ss           ss0
qqq          wwww
nn77         qqee

我要删除以下行：

具有数字
以nn
少于两个字符

我已经尝试过了：

df[~df.value1.str.contains(r'\d')]

但这不能满足我的所有需求。解决这个问题的最有效方法是什么？

非常感谢您

Answer 1

您只需要使用OR完善您的正则表达式即可匹配任何条件。

r'(\d)|(^nn)|(^.?$)'

这是：

\d（包含数字）

OR

^nn以nn开头

OR

^.?$表示0-1个字符（少于两个字符）。

尝试一下：

import pandas as pd
from io import StringIO

df = pd.read_csv(StringIO("""
value1       value2
aa7bbc       aaaa
ss           ss0
qqq          wwww
nn77         qqee"""), sep=r"\s+")

df = df[~df.value1.str.contains(r'(\d)|(^nn)|(^.?$)')]

print(df)

输出：

  value1 value2
1     ss    ss0
2    qqq   wwww

Answer 2

使用运算符根据条件进行过滤

Base

Answer 3

  tb <- tibble(
  tbx = c(0, 0, 0, 1, 1, 2, 3, 3, 3, 3, 4, 4, 9, 15, 18, 18, 19, 19, 20, 20, 21, 22, 22, 23),
  tby = c("g","g","g","g","g","g","g","g","g","g","g","g","t","t","g","g","g","g","g","g","g","g","g","g")
)


ggplot(tb, aes(tbx, tby = ..ndensity..)) +
  geom_histogram(bins = 25, aes(fill = tby)) +
  scale_fill_manual(values = c("red", "grey"))

Answer 4

这是一种实现方法：

mask_no_digit =( ~df.value1.str.contains(r'\d')) & (~df.value2.str.contains(r'\d'))
mask_no_nn = (~df['value1'].str.startswith('nn')) & (~df['value2'].str.startswith('nn'))
mask_no_2_characters = (~df['value1'].str.len()<=2 ) & (~df['value2'].str.len()<=2)

df[mask_no_digit & mask_no_nn & mask_no_2_characters]

输出：

  value1 value2
2    qqq   wwww

删除熊猫数据框中具有特殊值的行

4 个答案: