我正在嘗試用 1 列值和 1 列精度對 DataFrame 進行舍入。>>> df = pd.DataFrame({'value': [1.111, 2.222, 3.333, 4.444], 'precision': [1,2,2,1]})>>> df precision value0 1 1.1111 2 2.2222 2 3.3333 1 4.444要創建rounded這樣的列：>>> df precision value rounded0 1 1.111 1.11 2 2.222 2.222 2 3.333 3.333 1 4.444 4.4我嘗試了直觀的解決方案：>>> df['rounded'] = round(df['value'], df['precision'])Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/Users/Drew/Library/Python/2.7/lib/python/site-packages/pandas/core/series.py", line 93, in wrapper "{0}".format(str(converter)))TypeError: cannot convert the series to <type 'float'>和>>> df['rounded'] = df['value'].round(df['precision'])Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/Users/Drew/Library/Python/2.7/lib/python/site-packages/pandas/core/series.py", line 1999, in round result = com.values_from_object(self).round(decimals) File "/Users/Drew/Library/Python/2.7/lib/python/site-packages/pandas/core/series.py", line 93, in wrapper "{0}".format(str(converter)))TypeError: cannot convert the series to <type 'int'>有沒有辦法在不遍歷每一行的情況下做到這一點？
2 回答
慕無忌1623718
TA貢獻1744條經驗 獲得超4個贊
In [45]: df.apply(lambda x: round(x["value"], int(x["precision"])), axis=1)
Out[45]:
0 1.10
1 2.22
2 3.33
3 4.40
拉丁的傳說
TA貢獻1789條經驗 獲得超8個贊
使用列表理解將變量傳遞給np.round
df = pd.DataFrame({'value': [1.111, 2.222, 3.333, 4.444], 'precision': [1,2,3,1]})
print(df)
value precision
0 1.111 1
1 2.222 2
2 3.333 3
3 4.444 1
df['rounded'] = [np.around(x,y) for x,y in zip(df['value'],df['precision'])]
print(df)
value precision rounded
0 1.111 1 1.100
1 2.222 2 2.220
2 3.333 3 3.333
3 4.444 1 4.400
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