问题描述:

It's a little bit weird that I used nested loop, but it failed, it shows 'numpy.ndarray' object is not callable. So, does it have a better way to adjust each data in column data or row?

For example:

df

 a b c d

A 1 3 4 7

B 2 3 5 1

C 1 5 6 8

D 2 1 7 9

How can I add a number, such as

num = 1

And I wanna add num to each data in column 'c', like this:

 a b c d

A 1 3 5 7

B 2 3 6 1

C 1 5 7 8

D 2 1 8 9

Or I wanna add num to each data in row 'C', like this:

 a b c d

A 1 3 4 7

B 2 3 5 1

C 2 6 8 9

D 2 1 7 9

How can this work? Use nested loop like

for row in df.index:

for row in df['c']

Or

for row in df.index:

df.ix[row, 'c'] = df.ix[row, 'c'] + num

Can somebody help me check it out? Thanks!!!

网友答案:
df.loc[:, 'c'] += 1
df.loc['C', :] += 1
网友答案:

Well actually you can do this in a simplier way:

df['c'] += 1
df.ix['C'] += 1

It is simplier, innit?

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