[英]Create a new pandas dataframe column based on other column of the dataframe
I have a Dataframe that consists in 2 columns:我有一个包含 2 列的数据框:
'String' -> numpy array like [47, 0, 49, 12, 46] 'String' -> numpy 数组,如 [47, 0, 49, 12, 46]
'Is Isogram' -> 1 or 0 “是等值线图”-> 1 或 0
String Is Isogram
0 [47, 0, 49, 12, 46] 1
1 [43, 50, 22, 1, 13] 1
2 [10, 1, 24, 22, 16] 1
3 [2, 24, 3, 24, 51] 0
4 [40, 1, 41, 18, 3] 1
I would like to create another column, with the value 'Is Isogram' appended in the 'String' array, something like this:我想创建另一列,在 'String' 数组中附加值 'Is Isogram',如下所示:
String Is Isogram IsoString
0 [47, 0, 49, 12, 46] 1 [47, 0, 49, 12, 46, 1]
1 [43, 50, 22, 1, 13] 1 [43, 50, 22, 1, 13, 1]
2 [10, 1, 24, 22, 16] 1 [10, 1, 24, 22, 16, 1]
3 [2, 24, 3, 24, 51] 0 [2, 24, 3, 24, 51, 0]
4 [40, 1, 41, 18, 3] 1 [40, 1, 41, 18, 3, 1]
I've tried using the apply function with a lambda:我已经尝试使用带有 lambda 的 apply 函数:
df[''IsoString] = df.apply(lambda x: np.append(x['String'].values, x['Is Isogram'].values, axis=1))
But it throws me a KeyError that i don't really understand但它给我抛出了一个我不太理解的 KeyError
KeyError: ('String', 'occurred at index String')
How can i takle this problem?我该如何解决这个问题?
There is problem axis=1
is called for np.append
instead .apply
function:有问题
axis=1
被调用np.append
而不是.apply
函数:
df['IsoString'] = df.apply(lambda x: np.append(x['String'], x['Is Isogram']), axis=1)
Better/faster is use numpy.hstack
if same length of each lists in String
:如果
String
中每个列表的长度相同,则使用numpy.hstack
更好/更快:
arr = np.hstack((np.array(df['String'].tolist()), df['Is Isogram'].values[:, None]))
print (arr)
[[47 0 49 12 46 1]
[43 50 22 1 13 1]
[10 1 24 22 16 1]
[ 2 24 3 24 51 0]
[40 1 41 18 3 1]]
df['IsoString'] = arr.tolist()
print (df)
String Is Isogram IsoString
0 [47, 0, 49, 12, 46] 1 [47, 0, 49, 12, 46, 1]
1 [43, 50, 22, 1, 13] 1 [43, 50, 22, 1, 13, 1]
2 [10, 1, 24, 22, 16] 1 [10, 1, 24, 22, 16, 1]
3 [2, 24, 3, 24, 51] 0 [2, 24, 3, 24, 51, 0]
4 [40, 1, 41, 18, 3] 1 [40, 1, 41, 18, 3, 1]
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