迭代 Pandas 中的前 N 行
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Iterate over first N rows in pandas
提问by David542
What is the suggested way to iterate over the rows in pandas like you would in a file? For example:
像在文件中一样迭代 Pandas 中的行的建议方法是什么？例如：
LIMIT = 100
for row_num, row in enumerate(open('file','r')):
print (row)
if row_num == LIMIT: break
I was thinking to do something like:
我正在考虑做类似的事情：
for n in range(LIMIT):
print (df.loc[n].tolist())
Is there a built-in way to do this though in pandas?
在Pandas中是否有内置的方法来做到这一点？
回答by knh190
回答by timgeb
You can islicethe iterator iterrows(or itertuples) produces.
您可以islice使用迭代器iterrows（或itertuples）生成。
from itertools import islice
LIMIT = 100
# iterrows and unpacking
for idx, data in islice(df.iterrows(), LIMIT):
# do stuff
# itertuples, no unpacking
for row in islice(df.itertuples(), LIMIT):
# do stuff
回答by meW
You have values, itertuplesand iterrowsout of which itertuplesperforms best as benchmarked by fast-pandas.
你有values，itertuples和iterrows外面itertuples表现最好由基准快大Pandas。
回答by Joe Halliwell
You can use iterools.isliceto take the first nitems from iterrows:
您可以使用从以下位置iterools.islice获取第一n项iterrows：
import itertools
limit = 5
for index, row in itertools.islice(df.iterrows(), limit):
...
回答by gorjan
Since you said that you want to use something like an if I would do the following:
既然你说你想使用类似的东西，如果我会做以下事情：
limit = 2
df = pd.DataFrame({"col1": [1,2,3], "col2": [4,5,6], "col3": [7,8,9]})
df[:limit].loc[df["col3"] == 7]
This would select the first two rows of the data frame, then return the rows out of the first two rows that have a value for the col3equal to 7. Point being you want to use iterrowsonly in very very specific situations. Otherwise, the solution can be vectorized.
这将选择数据框的前两行，然后返回前两行中具有col3等于 7的值的行。重点是您只想iterrows在非常非常特定的情况下使用。否则，可以将解向量化。
I don't know what exactly are you trying to achieve so I just threw a random example.
我不知道你到底想达到什么目的，所以我只是随便举了一个例子。
回答by Tim
If you must iterate over the dataframe, you should use the iterrows()method:
如果必须遍历数据帧，则应使用以下iterrows()方法：
for index, row in df.iterrows():
...
