如何根据包含特定值的行(在任何列中)过滤数据框 [英] How can one filter a dataframe based on rows containing specific value (in any of the columns)

问题描述

我需要限制数据集，使其仅返回包含特定字符串的行，但是，该字符串可以存在于许多(8)列中.

I need to limit a dataset so that it returns only rows that contain specific string, however, that string can exist in many (8) of the columns.

我该怎么做?我已经看过str.isin方法，但是它为单行返回了一个系列.如何删除任何一列中包含字符串的任何行.

How can I do this? Ive seen str.isin methods, but it returns a single series for a single row. How can I remove any rows that contain the string in ANY of the columns.

示例代码 如果我有由

 import pandas as pd
    data = {'year': [2011, 2012, 2013, 2014, 2014, 2011, 2012, 2015], 
        'year2': [2012, 2016, 2015, 2015, 2012, 2013, 2019, 2016],
        'reports': [52, 20, 43, 33, 41, 11, 43, 72]}
    df = pd.DataFrame(data, index = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'])
    df    

   year  year2  reports
a  2011   2012       52
b  2012   2016       20
c  2013   2015       43
d  2014   2015       33
e  2014   2012       41
f  2011   2013       11
g  2012   2019       43
h  2015   2016       72

我希望代码删除所有不包含值2012的行.请注意，在我的实际数据集中，它是一个字符串，而不是一个int(它是人的名字) 因此，在上面的代码中，它将删除c, d, f, and h.

I want the code to remove rows all rows that do not contain the value 2012. Note that in my actual dataset, it is a string, not an int (it is peoples names) so in the above code it would remove rows c, d, f, and h.

推荐答案

，您可以使用 df.any 在axis=1上:

df[df.eq('2012').any(1)] #for year as string

或者:

df[df.eq(2012).any(1)] #for year as int

---

   year  year2  reports
a  2011   2012       52
b  2012   2016       20
e  2014   2012       41
g  2012   2019       43

这篇关于如何根据包含特定值的行(在任何列中)过滤数据框的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！