译（五十九）-Pandas dataframe转PyTorch tensor

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Pandas dataframe 转 PyTorch tensor

• M. Fabio asked:

  • 我想用 PyTorch 对 pandas dataframe df 训练一个简单的神经网络。

  • 其中一列是 Target，表示网络的训练目标，怎么用它作为 PyTorch 的输入？

  • 我试了下面这个但是不管用：

  • import pandas as pd
    import torch.utils.data as data_utils
    #
    target = pd.DataFrame(df['Target'])
    train = data_utils.TensorDataset(df, target)
    train_loader = data_utils.DataLoader(train, batch_size=10, shuffle=True)

• Answers:

  • MBT - vote: 62

  • 你好像没把确切的需求写在文中，所以我就按你的标题来回答，也就是转换 DataFrame 为 Tensor。

  • 你的数据也没给出，那我以浮点数为例。

  • 转换 Pandas dataframe 为 PyTorch tensor？

  • import pandas as pd
    import torch
    import random
    # 
    # creating dummy targets (float values)
    targets_data = [random.random() for i in range(10)]
    # 
    # creating DataFrame from targets_data
    targets_df = pd.DataFrame(data=targets_data)
    targets_df.columns = ['targets']
    #
    # creating tensor from targets_df 
    torch_tensor = torch.tensor(targets_df['targets'].values)
    #
    # printing out result
    print(torch_tensor)

  • 输出：

  • tensor([ 0.5827,  0.5881,  0.1543,  0.6815,  0.9400,  0.8683,  0.4289,
           0.5940,  0.6438,  0.7514], dtype=torch.float64)

  • PyTorch 0.4.0 环境下测试。

  • 希望能帮到你，还有问题请追问。:)

  • Allen Qin - vote: 23

  • 试试这个行不行（基于你给的代码）

  • train_target = torch.tensor(train['Target'].values.astype(np.float32))
    train = torch.tensor(train.drop('Target', axis = 1).values.astype(np.float32)) 
    train_tensor = data_utils.TensorDataset(train, train_target) 
    train_loader = data_utils.DataLoader(dataset = train_tensor, batch_size = batch_size, shuffle = True)

  • Anh-Thi DINH - vote: 12

  • 下面的函数可以转换任意的 Pandas dataframe/series 为 PyTorch tensor。

  • import pandas as pd
    import torch
    #
    # determine the supported device
    def get_device():
      if torch.cuda.is_available():
          device = torch.device('cuda:0')
      else:
          device = torch.device('cpu') # don't have GPU 
      return device
    #
    # convert a df to tensor to be used in pytorch
    def df_to_tensor(df):
      device = get_device()
      return torch.from_numpy(df.values).float().to(device)
    #
    df_tensor = df_to_tensor(df)
    series_tensor = df_to_tensor(series)

Convert Pandas dataframe to PyTorch tensor?

• M. Fabio asked:

  • I want to train a simple neural network with PyTorch on a pandas dataframe df.
    我想用 PyTorch 对 pandas dataframe df 训练一个简单的神经网络。

  • One of the columns is named Target, and it is the target variable of the network. How can I use this dataframe as input to the PyTorch network?
    其中一列是 Target，表示网络的训练目标，怎么用它作为 PyTorch 的输入？

  • I tried this, but it doesn\'t work:
    我试了下面这个但是不管用：

  • import pandas as pd
    import torch.utils.data as data_utils
    #
    target = pd.DataFrame(df['Target'])
    train = data_utils.TensorDataset(df, target)
    train_loader = data_utils.DataLoader(train, batch_size=10, shuffle=True)

• Answers:

  • MBT - vote: 62

  • I\'m referring to the question in the title as you haven\'t really specified anything else in the text, so just converting the DataFrame into a PyTorch tensor.
    你好像没把确切的需求写在文中，所以我就按你的标题来回答，也就是转换 DataFrame 为 Tensor。

  • Without information about your data, I\'m just taking float values as example targets here.
    你的数据也没给出，那我以浮点数为例。

  • Convert Pandas dataframe to PyTorch tensor?
    转换 Pandas dataframe 为 PyTorch tensor？

  • import pandas as pd
    import torch
    import random
    # 
    # creating dummy targets (float values)
    targets_data = [random.random() for i in range(10)]
    # 
    # creating DataFrame from targets_data
    targets_df = pd.DataFrame(data=targets_data)
    targets_df.columns = ['targets']
    #
    # creating tensor from targets_df 
    torch_tensor = torch.tensor(targets_df['targets'].values)
    #
    # printing out result
    print(torch_tensor)

  • Output:
    输出：

  • tensor([ 0.5827,  0.5881,  0.1543,  0.6815,  0.9400,  0.8683,  0.4289,
           0.5940,  0.6438,  0.7514], dtype=torch.float64)

  • Tested with Pytorch 0.4.0.
    PyTorch 0.4.0 环境下测试。

  • I hope this helps, if you have any further questions - just ask. 🙂
    希望能帮到你，还有问题请追问。:)

  • Allen Qin - vote: 23

  • Maybe try this to see if it can fix your problem(based on your sample code)?
    试试这个行不行（基于你给的代码）

  • train_target = torch.tensor(train['Target'].values.astype(np.float32))
    train = torch.tensor(train.drop('Target', axis = 1).values.astype(np.float32)) 
    train_tensor = data_utils.TensorDataset(train, train_target) 
    train_loader = data_utils.DataLoader(dataset = train_tensor, batch_size = batch_size, shuffle = True)

  • Anh-Thi DINH - vote: 12

  • You can use below functions to convert any dataframe or pandas series to a pytorch tensor
    下面的函数可以转换任意的 Pandas dataframe/series 为 PyTorch tensor。

  • import pandas as pd
    import torch
    #
    # determine the supported device
    def get_device():
      if torch.cuda.is_available():
          device = torch.device('cuda:0')
      else:
          device = torch.device('cpu') # don't have GPU 
      return device
    #
    # convert a df to tensor to be used in pytorch
    def df_to_tensor(df):
      device = get_device()
      return torch.from_numpy(df.values).float().to(device)
    #
    df_tensor = df_to_tensor(df)
    series_tensor = df_to_tensor(series)