Question

我有一个主题XY坐标的csv文件。如果X坐标小于5，则删除了一些XY。这可以适用于任何玩家并随时间变化。（参见示例数据集）。

在此文件P2的开头，P7，P12，P17删除了数据。虽然，在整个文件中，每个玩家都会丢失数据。对于大约90％的文件，在任何时间点都会有至少4名玩家丢失数据。

 @Override 
public void onBindViewHolder(MyRecyclerViewAdapter.DataObjectHolder holder,int position {

holder.name.setText(mDataset.get(position).getName());
holder.regId.setText(mDataset.get(position).getRegId());
holder.roomNo.setText(mDataset.get(position).getRoomNo());
holder.testImage = (ImageView)itemView.findViewById(R.id.log)
holder.testImage.setOnClickListener(new View.OnClickListener()
    {
        @Override
        public void onClick(View v) {
         name.setImageResource(Anything you want);


}

因为缺少数据我试图 0 10:39.2 65.75 45.10 1 10:39.3 65.77 45.16 2 10:39.4 65.78 45.24 3 10:39.5 65.78 45.33 4 10:39.6 65.78 45.33 5 10:39.7 65.75 45.44 6 10:39.8 65.72 45.56 7 10:39.9 65.72 45.56 8 10:40.0 65.73 45.90 9 10:40.1 65.73 46.09 10 10:40.2 65.76 46.27 11 10:40.3 65.81 46.43 12 10:40.4 65.87 46.58 13 10:40.5 65.91 46.69 14 10:40.6 65.94 46.80 15 10:40.7 65.95 46.93 16 10:40.8 65.93 47.09 17 10:40.9 65.92 47.23 功能，则会收到try: 读取csv文件。如果我删除了Frame Time P1_X P2_Y P2_X P2_Y P3_X P3_Y P4_X P4_Y P5_X P5_Y P6_X P6_Y P7_X P7_Y P8_X P8_Y P9_X P9_Y P10_X P10_Y P11_X P11_Y P12_X P12_Y 73.74 -3.52 61.91 41.80 67.07 -24.62 77.14 -22.98 93.95 3.51 56.52 28.44 70.21 11.06 73.08 -35.54 69.79 45.73 73.34 29.26 64.73 -40.69 70.90 6.11 70.94 -45.11 42.78 3.00 61.77 -1.05 72.07 38.62 73.69 -3.35 61.70 41.79 67.19 -24.59 77.17 -23.03 93.90 3.53 56.54 28.38 70.20 11.00 73.15 -35.48 69.79 45.86 73.20 29.30 64.96 -40.77 70.91 6.10 71.04 -45.29 42.84 3.02 61.82 -0.99 72.12 38.71 73.63 -3.17 61.70 41.79 67.32 -24.56 77.20 -23.05 93.83 3.55 56.59 28.31 70.20 10.92 73.20 -35.41 69.79 45.86 73.03 29.36 65.19 -40.84 70.91 6.10 71.15 -45.50 42.91 3.04 61.89 -0.91 72.16 38.80 73.57 -3.00 61.49 41.78 67.45 -24.50 77.25 -23.07 93.75 3.57 56.59 28.31 70.21 10.83 73.25 -35.33 69.77 46.01 72.86 29.43 65.45 -40.86 70.90 6.09 71.15 -45.50 43.01 3.08 61.98 -0.81 72.19 38.86 73.51 -2.86 61.32 41.76 67.45 -24.50 77.31 -23.09 93.64 3.60 56.65 28.22 70.23 10.72 73.29 -35.22 69.72 46.17 72.69 29.51 65.75 -40.84 70.88 6.08 71.24 -45.71 43.11 3.12 62.06 -0.70 72.22 38.90 73.51 -2.86 61.20 41.73 67.59 -24.37 77.38 -23.10 93.52 3.63 56.73 28.09 70.25 10.59 73.29 -35.22 69.68 46.33 72.49 29.60 66.06 -40.84 70.86 6.05 71.31 -45.91 43.22 3.14 62.13 -0.59 72.26 38.92 73.45 -2.72 61.08 41.71 67.72 -24.19 77.44 -23.12 93.39 3.69 56.80 27.91 70.27 10.45 73.34 -35.08 69.66 46.48 72.27 29.67 66.36 -40.87 70.86 6.01 71.39 -46.09 43.35 3.17 62.20 -0.47 72.29 38.93 73.34 -2.48 60.97 41.72 67.92 -23.76 77.51 -23.13 93.23 3.75 56.80 27.91 70.30 10.31 73.40 -34.76 69.64 46.63 72.01 29.74 66.62 -40.93 70.85 5.96 71.39 -46.09 43.51 3.18 62.27 -0.35 72.31 38.93 73.34 -2.48 60.86 41.72 67.92 -23.76 77.51 -23.13 93.05 3.80 56.91 27.47 70.30 10.31 73.40 -34.76 69.63 46.76 72.01 29.74 66.82 -41.06 70.83 5.88 71.53 -46.45 43.68 3.20 62.27 -0.35 72.29 38.92 73.29 -2.39 60.74 41.70 68.00 -23.52 77.60 -23.12 92.83 3.86 56.99 27.23 70.35 10.17 73.43 -34.58 69.64 46.88 71.72 29.80 66.99 -41.22 70.80 5.79 71.60 -46.63 43.86 3.23 62.34 -0.22 72.22 38.89 73.22 -2.32 60.60 41.65 68.07 -23.24 77.71 -23.05 92.83 3.86 57.14 26.98 70.43 10.05 73.47 -34.38 69.68 46.96 71.42 29.85 67.16 -41.38 70.77 5.70 71.64 -46.80 44.04 3.28 62.43 -0.08 72.13 38.86 73.12 -2.28 60.43 41.60 68.12 -22.93 77.83 -22.94 92.58 3.89 57.32 26.72 70.54 9.92 73.50 -34.16 69.75 46.99 71.08 29.89 67.16 -41.38 70.74 5.62 71.67 -46.96 44.21 3.33 62.54 0.09 72.03 38.84 72.98 -2.29 60.24 41.55 68.15 -22.57 77.94 -22.76 92.30 3.93 57.52 26.45 70.67 9.78 73.50 -33.91 69.85 47.00 70.72 29.91 67.31 -41.57 70.70 5.52 71.73 -47.15 44.37 3.40 62.66 0.24 72.03 38.84 72.80 -2.32 60.07 41.49 68.17 -22.18 78.01 -22.53 91.99 3.98 57.71 26.18 70.81 9.60 73.49 -33.68 69.97 47.03 70.33 29.92 67.45 -41.78 70.64 5.38 71.81 -47.35 44.37 3.40 62.80 0.40 71.96 38.81 72.60 -2.34 59.93 41.43 68.19 -21.77 78.05 -22.27 91.69 4.03 57.89 25.90 70.96 9.42 73.47 -33.47 70.10 47.09 69.93 29.93 67.54 -41.96 70.56 5.20 71.86 -47.53 44.54 3.50 62.98 0.58 71.91 38.77 72.36 -2.36 59.80 41.38 68.18 -21.32 78.08 -21.99 91.38 4.09 58.11 25.63 71.11 9.26 73.41 -33.26 70.24 47.15 69.50 29.91 67.58 -42.15 70.56 5.20 71.86 -47.69 44.54 3.50 63.16 0.77 71.91 38.77 72.10 -2.34 59.65 41.36 68.16 -20.86 78.11 -21.68 91.09 4.17 58.35 25.38 71.23 9.13 73.31 -33.05 70.38 47.20 69.07 29.84 67.56 -42.32 70.44 5.00 71.81 -47.84 45.00 3.79 63.34 0.97 71.80 38.60 71.85 -2.28 59.47 41.37 68.11 -20.41 78.11 -21.37 90.81 4.27 58.59 25.12 71.33 9.00 73.22 -32.84 70.52 47.26 68.63 29.75 67.47 -42.51 70.28 4.78 71.75 -47.97 45.26 3.94 63.52 1.14 71.73 38.46 except:。



Type Error stating I couldn't convert string to float

但是，当我使用此代码时，它只会在每行数据存在时将值返回到列表中。如上所述，这仅发生在文件的大约10％。我使用xy来创建每个点的散点图，因此不能更改为0,0因为这将创建一个错误的数据点。如何更改代码，以便在未删除玩家数据时返回xy值。

Answer 1

您可以在循环之前定义自己的转换：

def convert_float(x);
    if x:            # equivalent to if x == ''
        return float(x)
    else:
        return 0.0   # or set the default value you expect to replace the missing data with.

结合@juanpa.arrivillaga's excellent suggestion，将visual.append行更改为：

visual[0].append(list(map(convert_float, row[3::2]))
visual[1].append(list(map(convert_float, row[2::2]))

此外，我不确定你的n + = 1行应该做什么......如果你只是想跳过第一行（标题），只需这样做：

def convert_float(x);
    if x:
        return float(x)
    else:
        return 0.0

for i, row in enumerate(readCSV):
    if n > 0:
        visual[0].append(list(map(convert_float, row[3::2]))
        visual[1].append(list(map(convert_float, row[2::2]))

读取csv时删除值并返回列表

1 个答案: