Python TypeError：尝试对数据帧进行数学运算时，无法将系列转换为 <class 'int'>
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Python TypeError: cannot convert the series to <class 'int'> when trying to do math on dataframe
提问by Jassica Mao
I have a data frame that looks something like this:
我有一个看起来像这样的数据框：
defaultdict(<class 'list'>, {'XYF': TimeUS GyrX GyrY GyrZ AccX \
0 207146570 0.000832914 0.001351716 -0.0004189798 -0.651183
1 207186671 0.001962787 0.001242457 -0.0001859666 -0.6423497
2 207226791 9.520243E-05 0.001076498 -0.0005664826 -0.6360412
3 207246474 0.0001093059 0.001616917 0.0003615251 -0.6342875
4 207286244 0.001412051 0.0007565815 -0.0003780428 -0.637755
[103556 rows x 12 columns], 'DAR': TimeUS RSSI RemRSSI TxBuf Noise RemNoise RxErrors Fixed
0 208046965 159 161 79 25 29 0 0
1 208047074 159 161 79 25 29 0 0
2 208927455 159 159 91 28 28 0 0
3 208927557 159 159 91 28 28 0 0
[4136 rows x 8 columns], 'NK2': TimeUS IVN IVE IVD IPN IPE IPD IMX IMY IMZ IYAW \
0 207147350 -0.02 0.02 0.00 -0.02 0.01 0.20 0 0 0 1.94
1 207187259 -0.02 0.02 0.00 -0.02 0.01 0.20 0 0 0 1.94
2 207227559 -0.02 0.02 0.00 -0.02 0.01 0.14 0 0 0 1.77
3 207308304 0.02 0.02 0.00 -0.01 0.01 -0.05 0 0 0 1.77
4 207347766 0.02 0.02 0.00 -0.01 0.01 -0.05 0 0 0 0.82
I first separated the column I want to do math with:
我首先将要进行数学运算的列分开：
new_time = dfs['XYF']['TimeUS']
Then I have tried several things to do some math on it but I had no luck. First I just treated it like a list. so
然后我尝试了几件事来做一些数学运算，但我没有运气。首先，我只是把它当作一个列表。所以
new_time_F = new_time / 1000000
That didn't work, gave me a float error of:
那没有用，给了我一个浮动错误：
TypeError: unsupported operand type(s) for /: 'str' and 'int'
so I did this:
所以我这样做了：
new_time_F = float (new_time) / 1000000
This give me an error:
这给了我一个错误：
TypeError: cannot convert the series to <class 'float'>
I have no idea where to go from here.
我不知道从这里去哪里。
回答by AlexG
What if you do this (as was suggested earlier):
如果你这样做（正如之前建议的那样）：
new_time = dfs['XYF']['TimeUS'].astype(float)
new_time_F = new_time / 1000000
回答by languitar
Seems your initial data contains strings and not numbers. It would probably be best to ensure that the data is already of the required type up front.
似乎您的初始数据包含字符串而不是数字。最好预先确保数据已经是所需的类型。
However, you can convert strings to numbers like this:
但是，您可以将字符串转换为数字，如下所示：
pd.Series(['123', '42']).astype(float)
instead of float(series)
代替 float(series)
回答by kashanipour
You can use from the pd.to_numeric(s)
您可以从 pd.to_numeric(s)
