Question

我正在尝试将A中dataframe的列的dtype（float64）从int转换为df['A'].astype(numpy.int64)，

但在此之后，float64仍然以@Override public boolean pinch(Vector2 initialPointer1, Vector2 initialPointer2, Vector2 pointer1, Vector2 pointer2) { // Calculate distances float initialDistance = initialPointer1.dst(initialPointer2); float distance = pointer1.dst(pointer2); // Calculate pinch coordinates float initialPinchX = (initialPointer1.x + initialPointer2.x) / 2; float initialPinchY = (initialPointer1.y + initialPointer2.y) / 2; float pinchX = (pointer1.x + pointer2.x) / 2; float pinchY = (pointer1.y + pointer2.y) / 2; // This to avoid first time zooming or panning horrible behavior if (lastZoomDistance == 0) { lastZoomDistance = initialDistance; } if (lastPinchX == lastPinchY && lastPinchX == 0) { lastPinchX = initialPinchX; lastPinchY = initialPinchY; } // Zoom float distanceDifference = distance - lastZoomDistance; camera.zoom -= distanceDifference / 300; // Pan float deltaX = (pinchX - lastPinchX) * camera.zoom; float deltaY = (pinchY - lastPinchY) * camera.zoom; camera.translate(-deltaX, deltaY); // We need to update these for future calculations lastZoomDistance = distance; lastPinchX = (pointer1.x + pointer2.x) / 2; lastPinchY = (pointer1.y + pointer2.y) / 2; return false; }作为dtype。我想知道如何解决这个问题。

Answer 1

您的输出似乎没有分配回来，所以需要：

df['A'] = df['A'].astype(numpy.int64)

如果NaNs使用fillna将其转换为int：

df['A'] = df['A'].fillna(0).astype(numpy.int64)

或者NaN列A列中的df = df.dropna('A') df['A'] = df['A'].astype(numpy.int64) s删除所有行：

switch (this.state.selectedOption) {
  case 'fifthOption':
    return <FifthComponent />;
   /*use span instead of div in every odd option,
     so they mixed up "span - div - span - div" and so on*/
  case 'firstOption': // 
  case 'thirdOption':
    return (
      <span className="wrapper">
        <span className="title">{this.state.selectedOption}</span>
      </span>);
  default:
    return (
      <div className="wrapper">
        <span className="title">{this.state.selectedOption}</span>
      </div>);
}

Answer 2

如果您有NaN值，那么Pandas无法将其转换为int。

但很可能你只是没有将结果分配回A专栏（正如@jezrael已经说过的那样）。

如果您尝试将NaN＆＃39转换为整数，则会出现以下异常：

In [4]: df = pd.DataFrame({'A':[1,2,np.nan,4]})

In [5]: df
Out[5]:
     A
0  1.0
1  2.0
2  NaN
3  4.0

In [6]: df['A'] = df['A'].astype(np.int64)
...
skipped
...
ValueError: Cannot convert non-finite values (NA or inf) to integer

pandas将float64转换为int

2 个答案: