pandas 使用 iterrows() 时如何通过索引访问列
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How to access column via index when using iterrows()
提问by Xoul
I want to know how I can access columns using index rather than name when using iterrowsto traverse DataFrames.
我想知道在iterrows用于遍历 DataFrame时如何使用索引而不是名称访问列。
This code is most I could find:
这段代码是我能找到的最多的：
for index, row in df.iterrows():
print row['Date']
This is another approach I took to traverse, but it seems very slow:
这是我用来遍历的另一种方法，但看起来很慢：
for i in df.index:
for j in range(len(df.columns)):
df.ix[i,j] = 0
采纳答案by Xoul
I figured it out. Iterate for i to number of columnsand use ias index to access columns:
我想到了。迭代i to number of columns并i用作索引来访问列：
for i in range(len(df.columns)):
for index, row in df.iterrows():
print row.ix[i]
回答by Colonel Beauvel
You can use ixto access by index:
您可以使用ix按索引访问：
In [67]: df
Out[67]:
A B
0 test1 1
1 test2 4
2 test3 1
3 test4 2
In [68]: df.ix[:,1]
Out[68]:
0 1
1 4
2 1
3 2
Name: B, dtype: int64
Updating your code with first column:
使用第一列更新您的代码：
for index, row in df.iterrows():
row.ix[0]
