Question

您好，我正在学习数据科学，正在制作一个具有一些属性的大数据公司列表。

目前我的数据框数据看起来像这样。

    company_url company tag_line    product data
0   https://angel.co/billguard  BillGuard   The fastest smartest way to track your spendin...   BillGuard is a personal finance security app t...   New York City · Financial Services · Security ...
1   https://angel.co/tradesparq Tradesparq  The world's largest social network for global ...   Tradesparq is Alibaba.com meets LinkedIn. Trad...   Shanghai · B2B · Marketplaces · Big Data · Soc...
2   https://angel.co/sidewalk   Sidewalk    Hoovers (D&B) for the social era    Sidewalk helps companies close more sales to s...   New York City · Lead Generation · Big Data · S...
3   https://angel.co/pangia Pangia  The Internet of Things Platform: Big data mana...   We collect and manage data from sensors embedd...   San Francisco · SaaS · Clean Technology · Big ...
4   https://angel.co/thinknum   Thinknum    Financial Data Analysis Thinknum is a powerful web platform to value c...   New York City · Enterprise Software · Financia...

我希望使用某些关键字（例如“大数据”）对“数据”列进行排序，并使用行创建新的数据框。

我想首先找到拟合行，然后将它们放入列表并根据行列表对数据帧，数据进行排序，但第一部分出现错误。

我的代码：

comp_rows = []
a = ['Data','Analytics','Machine Learning','Deep','Mining']

for count, item in enumerate(data.data):
    if any(x in item for x in a):
        comp_rows.append(count)

错误：

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-174-afeee7d3d179> in <module>()
      3 
      4 for count, item in enumerate(data.data):
----> 5     if any(x in item for x in a):
      6         comp_rows.append(count)

<ipython-input-174-afeee7d3d179> in <genexpr>((x,))
      3 
      4 for count, item in enumerate(data.data):
----> 5     if any(x in item for x in a):
      6         comp_rows.append(count)

TypeError: argument of type 'float' is not iterable

有人可以帮我吗？

Answer 1

如果你的data.data是一个字符串列表，但在那里找到了一个浮点数，它会工作。尝试更换
if any(x in item for x in a): 与if any(x in str(item) for x in a):

基于多个关键字对Pandas数据帧上的行进行排序

1 个答案: