您好我正在学习数据科学，并且正在尝试从各个行业的公司列表中创建一个大数据公司列表。
我有一个大数据公司的行号列表，名为comp_rows。 现在，我正在尝试根据行号与过滤后的公司建立新的数据框。在这里，我需要向现有数据帧添加行，但是我收到了错误。有人可以帮忙吗？
我的数据框看起来像这样。
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...
我的代码如下：
bigdata_comp = DataFrame(data=None,columns=['company_url','company','tag_line','product','data'])
for count, item in enumerate(data.iterrows()):
for number in comp_rows:
if int(count) == int(number):
bigdata_comp.append(item)
错误：
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-234-1e4ea9bd9faa> in <module>()
4 for number in comp_rows:
5 if int(count) == int(number):
----> 6 bigdata_comp.append(item)
7
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/core/frame.pyc in append(self, other, ignore_index, verify_integrity)
3814 from pandas.tools.merge import concat
3815 if isinstance(other, (list, tuple)):
-> 3816 to_concat = [self] + other
3817 else:
3818 to_concat = [self, other]
TypeError: can only concatenate list (not "tuple") to list
答案 0 :(得分：2)
您似乎正在尝试根据索引（存储在名为comp_rows的变量中）过滤掉现有数据框。您可以使用loc而不使用循环来执行此操作，如下所示：
In [1161]: df1.head()
Out[1161]:
A B C D
a 1.935094 -0.160579 -0.173458 0.433267
b 1.669632 -1.130893 -1.210353 0.822138
c 0.494622 1.014013 0.215655 1.045139
d -0.628889 0.223170 -0.616019 -0.264982
e -0.823133 0.385790 -0.654533 0.582255
我们将获得带索引的行＆＃39; a＆＃39;＆＃39; b＆＃39;和＆＃39; c＆＃39;，对于所有列：
In [1162]: df1.loc[['a','b','c'],:]
Out[1162]:
A B C D
a 1.935094 -0.160579 -0.173458 0.433267
b 1.669632 -1.130893 -1.210353 0.822138
c 0.494622 1.014013 0.215655 1.045139
您可以阅读更多相关信息here.
关于您的代码：
1。
您无需遍历列表以查看其中是否存在项目：
使用in运算符。例如 -
In [1199]: 1 in [1,2,3,4,5]
Out[1199]: True
所以，而不是
for number in comp_rows:
if int(count) == int(number):
这样做
if number in comp_rows
2。
大熊猫append不会就地发生。您必须将结果存储到另一个变量中。请参阅here。
3
一次追加一行是做你想做的慢的方法。 而是将要添加的每一行保存到列表列表中，创建一个数据帧并一次性将其附加到目标数据帧。像这样......
temp = []
for count, item in enumerate(df1.loc[['a','b','c'],:].iterrows()):
# if count in comp_rows:
temp.append( list(item[1]))
## -- End pasted text --
In [1233]: temp
Out[1233]:
[[1.9350940285526077,
-0.16057932637141861,
-0.17345827000000605,
0.43326722021644282],
[1.66963201034217,
-1.1308932586268696,
-1.2103527446031515,
0.82213753819050794],
[0.49462218161377397,
1.0140133740187862,
0.2156547595968879,
1.0451391564351897]]
In [1236]: df2 = df1.append(pd.DataFrame(temp, columns=['A','B','C','D']))
In [1237]: df2
Out[1237]:
A B C D
a 1.935094 -0.160579 -0.173458 0.433267
b 1.669632 -1.130893 -1.210353 0.822138
c 0.494622 1.014013 0.215655 1.045139
d -0.628889 0.223170 -0.616019 -0.264982
e -0.823133 0.385790 -0.654533 0.582255
f -0.872135 2.938475 -0.099367 -1.472519
0 1.935094 -0.160579 -0.173458 0.433267
1 1.669632 -1.130893 -1.210353 0.822138
2 0.494622 1.014013 0.215655 1.045139
答案 1 :(得分：0)
替换以下行：
for count, item in enumerate(data.iterrows()):
通过
for count, (index, item) in enumerate(data.iterrows()):
甚至只是
for count, item in data.iterrows():