Python Pandas Dataframe条件If，Elif，Else [英] Python Pandas Dataframe Conditional If, Elif, Else

问题描述

在Python Pandas DataFrame中，如果搜索字词"列包含连接的竖线分隔列表中的任何可能的字符串，则尝试将特定标签应用于行.如果用熊猫其他语句，我该怎么做?

In a Python Pandas DataFrame, I'm trying to apply a specific label to a row if a 'Search terms' column contains any possible strings from a joined, pipe-delimited list. How can I do conditional if, elif, else statements with Pandas?

例如:

df = pd.DataFrame({'Search term': pd.Series(['awesomebrand inc', 'guy boots', 'ectoplasm'])})

brand_terms = ['awesomebrand', 'awesome brand']
footwear_terms = ['shoes', 'boots', 'sandals']

#Note: this does not work
if df['Search term'].str.contains('|'.join(brand_terms)):
  df['Label'] = 'Brand'
elif df['Search term'].str.contains('|'.join(footwear_terms)):
  df['Label'] = 'Footwear'
else:
  df['Label'] = '--'

所需输出示例:

Search Term          Label
awesomebrand inc     Brand
guy boots            Footwear
ectoplasm            --

我尝试将.any()附加到contains()语句的末尾，但是它将Brand标签应用到每一行.

I've tried appending .any() to the ends of the contains() statements but it applies the Brand label to every row.

我遇到的大多数示例都是在比较列值==是否等于(不是我想要的值)还是执行数字比较，而不是文本字符串比较.

Most of the examples I come across are comparing if a column value == is equal to (not what I want) or are performing numeric comparisons, not text string comparisons.

推荐答案

这是使用str.contains()和np.where()

In [26]:
np.where(df['Search term'].str.contains('|'.join(brand_terms)),
        'Brand',
         np.where(df['Search term'].str.contains('|'.join(footwear_terms)),
             'Footwear',
             '--'))

Out[26]:
array(['Brand', 'Footwear', '--'],
      dtype='|S8')

您可以像这样分配给df['Label']

In [27]: df['Label'] = np.where(df['Search term'].str.contains('|'.join(brand_terms)),
   ....:               'Brand',
   ....:               np.where(df['Search term'].str.contains('|'.join(footwear_terms)),
   ....:                       'Footwear',
   ....:                       '--'))

In [28]: df
Out[28]:
        Search term     Label
0  awesomebrand inc     Brand
1         guy boots  Footwear
2         ectoplasm        --

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