pandas - 如何使所有行数据删除相似数据并乘以浮点数
问题描述
如何分隔所有列？
df= df[['hlogUs_dB','hlogDs_dB']]
df
hlogUs_dB hlogDs_dB
0 109:-3.4,110:-3.4,111:-3.4,112:-3.5,113:-3.5,1... 5:-2.5,6:-2.5,7:-2.1,8:-2.0,9:-2.0,10:-2.0,11:...
1 109:-3.5,110:-3.5,111:-3.4,112:-3.4,113:-3.4,1... 5:-2.1,6:-2.0,7:-1.8,8:-1.8,9:-1.8,10:-1.8,11:...
2 109:-3.7,110:-3.7,111:-3.8,112:-3.8,113:-3.8,1... 5:-2.1,6:-2.0,7:-1.8,8:-1.8,9:-1.8,10:-1.8,11:...
3 109:-3.5,110:-3.6,111:-3.6,112:-3.6,113:-3.7,1... 5:-2.5,6:-2.5,7:-2.1,8:-2.0,9:-2.0,10:-2.0,11:...
4 109:-3.7,110:-3.8,111:-3.8,112:-3.8,113:-3.8,1... 5:-2.5,6:-2.5,7:-2.1,8:-2.1,9:-2.0,10:-2.1,11:...
... ... ...
165 109:-5.2,110:-5.3,111:-5.5,112:-5.7,113:-5.9,1... 5:-2.5,6:-2.5,7:-2.1,8:-2.1,9:-2.1,10:-2.2,11:...
166 109:-5.5,110:-5.6,111:-5.8,112:-6.1,113:-6.3,1... 5:-2.8,6:-2.7,7:-2.5,8:-2.5,9:-2.3,10:-2.5,11:...
167 109:-6.0,110:-6.2,111:-6.4,112:-6.7,113:-7.1,1... 5:-2.6,6:-2.5,7:-2.2,8:-2.2,9:-2.2,10:-2.3,11:...
168 109:-5.4,110:-5.5,111:-5.7,112:-5.9,113:-6.2,1... 5:-3.0,6:-3.0,7:-2.6,8:-2.5,9:-2.5,10:-2.5,11:...
169 109:-5.9,110:-6.1,111:-6.4,112:-6.6,113:-7.0,1... 5:-2.7,6:-2.5,7:-2.3,8:-2.2,9:-2.3,10:-2.3,11:...
170 rows × 2 columns
<之后我只使用分隔符拆分hlogUs_dB/>
df2 =df['hlogUs_dB'].str.split('[,:]',expand = True)
df2 = data.drop(["0"])
df2
结果 ：
0 1 2 3 4 5 6 7 8 9 ... 276 277 278 279 280 281 282 283 284 285
0 109 -3.4 110 -3.4 111 -3.4 112 -3.5 113 -3.5 ... 343 -4.3 344 -4.3 345 -4.2 346 -4.2 347 -4.2
1 109 -3.5 110 -3.5 111 -3.4 112 -3.4 113 -3.4 ... 343 -4.1 344 -4.2 345 -4.4 346 -4.4 347 -4.2
2 109 -3.7 110 -3.7 111 -3.8 112 -3.8 113 -3.8 ... 343 -4.2 344 -4.3 345 -4.3 346 -4.3 347 -4.3
3 109 -3.5 110 -3.6 111 -3.6 112 -3.6 113 -3.7 ... 343 -4.1 344 -4.1 345 -4.1 346 -4.1 347 -4.1
4 109 -3.7 110 -3.8 111 -3.8 112 -3.8 113 -3.8 ... 343 -4.2 344 -4.2 345 -4.2 346 -4.2 347 -4.3
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
165 109 -5.2 110 -5.3 111 -5.5 112 -5.7 113 -5.9 ... 343 -5.4 344 -5.3 345 -5.2 346 -5.1 347 -5.1
166 109 -5.5 110 -5.6 111 -5.8 112 -6.1 113 -6.3 ... 343 -5.5 344 -5.4 345 -5.3 346 -5.2 347 -5.2
167 109 -6.0 110 -6.2 111 -6.4 112 -6.7 113 -7.1 ... 343 -4.9 344 -4.9 345 -4.9 346 -4.9 347 -4.9
168 109 -5.4 110 -5.5 111 -5.7 112 -5.9 113 -6.2 ... 343 -5.9 344 -5.7 345 -5.7 346 -5.6 347 -5.6
169 109 -5.9 110 -6.1 111 -6.4 112 -6.6 113 -7.0 ... 343 -5.7 344 -5.7 345 -5.7 346 -5.6 347 -5.6
170 rows × 286 columns
之后，我想删除仅出现在偶数列上的相同数字。我设法找到了解决方案，但不知何故或更确切地说，它不符合我的喜好。
df2.drop(columns=[0,2,4,6,8,9,10,12,14,16,18,20,22,24,26,28,30,32,34,36])
df2
输出：
0 1 2 3 4 5 6 7 8 9 ... 276 277 278 279 280 281 282 283 284 285
0 109 -3.4 110 -3.4 111 -3.4 112 -3.5 113 -3.5 ... 343 -4.3 344 -4.3 345 -4.2 346 -4.2 347 -4.2
1 109 -3.5 110 -3.5 111 -3.4 112 -3.4 113 -3.4 ... 343 -4.1 344 -4.2 345 -4.4 346 -4.4 347 -4.2
2 109 -3.7 110 -3.7 111 -3.8 112 -3.8 113 -3.8 ... 343 -4.2 344 -4.3 345 -4.3 346 -4.3 347 -4.3
3 109 -3.5 110 -3.6 111 -3.6 112 -3.6 113 -3.7 ... 343 -4.1 344 -4.1 345 -4.1 346 -4.1 347 -4.1
4 109 -3.7 110 -3.8 111 -3.8 112 -3.8 113 -3.8 ... 343 -4.2 344 -4.2 345 -4.2 346 -4.2 347 -4.3
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
165 109 -5.2 110 -5.3 111 -5.5 112 -5.7 113 -5.9 ... 343 -5.4 344 -5.3 345 -5.2 346 -5.1 347 -5.1
166 109 -5.5 110 -5.6 111 -5.8 112 -6.1 113 -6.3 ... 343 -5.5 344 -5.4 345 -5.3 346 -5.2 347 -5.2
167 109 -6.0 110 -6.2 111 -6.4 112 -6.7 113 -7.1 ... 343 -4.9 344 -4.9 345 -4.9 346 -4.9 347 -4.9
168 109 -5.4 110 -5.5 111 -5.7 112 -5.9 113 -6.2 ... 343 -5.9 344 -5.7 345 -5.7 346 -5.6 347 -5.6
169 109 -5.9 110 -6.1 111 -6.4 112 -6.6 113 -7.0 ... 343 -5.7 344 -5.7 345 -5.7 346 -5.6 347 -5.6
170 rows × 286 columns
仍然显示与以前相同，我只希望奇数列与 8 和float4.3125 相乘。然后稍后数据将在相同的列上替换，这是我的大致想法。
df2*4.3125
结果包含错误。
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
~\anaconda3\lib\site-packages\pandas\core\ops\array_ops.py in na_arithmetic_op(left, right, op, str_rep)
148 try:
--> 149 result = expressions.evaluate(op, str_rep, left, right)
150 except TypeError:
~\anaconda3\lib\site-packages\pandas\core\computation\expressions.py in evaluate(op, op_str, a, b, use_numexpr)
207 if use_numexpr:
--> 208 return _evaluate(op, op_str, a, b)
209 return _evaluate_standard(op, op_str, a, b)
~\anaconda3\lib\site-packages\pandas\core\computation\expressions.py in _evaluate_numexpr(op, op_str, a, b)
120 if result is None:
--> 121 result = _evaluate_standard(op, op_str, a, b)
122
~\anaconda3\lib\site-packages\pandas\core\computation\expressions.py in _evaluate_standard(op, op_str, a, b)
69 with np.errstate(all="ignore"):
---> 70 return op(a, b)
71
TypeError: can't multiply sequence by non-int of type 'float'
During handling of the above exception, another exception occurred:
TypeError Traceback (most recent call last)
<ipython-input-24-424060d3aad6> in <module>
----> 1 df2*4.3125
~\anaconda3\lib\site-packages\pandas\core\ops\__init__.py in f(self, other, axis, level, fill_value)
717 self = self.fillna(fill_value)
718
--> 719 new_data = dispatch_to_series(self, other, op, str_rep)
720 return self._construct_result(new_data)
721
~\anaconda3\lib\site-packages\pandas\core\ops\__init__.py in dispatch_to_series(left, right, func, str_rep, axis)
376 # Get the appropriate array-op to apply to each block's values.
377 array_op = get_array_op(func, str_rep=str_rep)
--> 378 bm = left._data.apply(array_op, right=right)
379 return type(left)(bm)
380
~\anaconda3\lib\site-packages\pandas\core\internals\managers.py in apply(self, f, filter, **kwargs)
438
439 if callable(f):
--> 440 applied = b.apply(f, **kwargs)
441 else:
442 applied = getattr(b, f)(**kwargs)
~\anaconda3\lib\site-packages\pandas\core\internals\blocks.py in apply(self, func, **kwargs)
388 """
389 with np.errstate(all="ignore"):
--> 390 result = func(self.values, **kwargs)
391
392 if is_extension_array_dtype(result) and result.ndim > 1:
~\anaconda3\lib\site-packages\pandas\core\ops\array_ops.py in arithmetic_op(left, right, op, str_rep)
195 else:
196 with np.errstate(all="ignore"):
--> 197 res_values = na_arithmetic_op(lvalues, rvalues, op, str_rep)
198
199 return res_values
~\anaconda3\lib\site-packages\pandas\core\ops\array_ops.py in na_arithmetic_op(left, right, op, str_rep)
149 result = expressions.evaluate(op, str_rep, left, right)
150 except TypeError:
--> 151 result = masked_arith_op(left, right, op)
152
153 return missing.dispatch_fill_zeros(op, left, right, result)
~\anaconda3\lib\site-packages\pandas\core\ops\array_ops.py in masked_arith_op(x, y, op)
110 if mask.any():
111 with np.errstate(all="ignore"):
--> 112 result[mask] = op(xrav[mask], y)
113
114 result, _ = maybe_upcast_putmask(result, ~mask, np.nan)
TypeError: can't multiply sequence by non-int of type 'float'
我被困在该地区，并在 Stack Overflow、youtube 上搜索了关于浮点数乘法的基本知识，但我认为我的关键字与这些想法不符。
解决方案
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