name 'pd_datetime' is not defined

It seems like you are trying to use the function pd_datetime() but the name 'pd_datetime' is not defined. This error message usually occurs when you have not imported the necessary libraries or there is a typo in the function name. To use pd_datetime(), you need to import the pandas library using the following code:

import pandas as pd

Then you can use the pd_datetime() function to convert a string to a datetime object. For example:

date_string = '2021-03-23'
date_object = pd_datetime(date_string)

This will convert the string '2021-03-23' to a datetime object.

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Traceback (most recent call last): File "task1/test1.py", line 32, in <module> choose_data=tk.choose_data(data) File "/data/workspace/myshixun/task1/task1.py", line 16, in choose_data data_time=pd_datetime[date.time] NameError: name 'pd_datetime' is not defined我该怎么修改

这个错误提示是因为代码中使用了一个不存在的变量`pd_datetime`。我猜测你的代码中想要使用`pandas`库中的`to_datetime`函数将时间字符串转换为`datetime`类型，并且这个函数名字写错了。你需要将`pd_datetime`改成`pd.to_datetime`，并且将`date.time`改成`data['time']`，如下所示：

import pandas as pd
import numpy as np

def choose_data(data):
    # 选择变量'user_id', 'time', 'model_id', 'type', 'cate', 'brand',
    # 选取time在2016-02-01及以后的数据（包含2016-02-01）且type=6，
    # 数据类型如下：
    #    user_id  sku_id                 time  model_id  type  cate  brand
    # 0   266079  138778  2016-01-31 23:59:02       NaN     1     8    403
    # 1   266079  138778  2016-01-31 23:59:03       0.0     6     8    403
    # 2   200719   61226  2016-01-31 23:59:07       NaN     1     8     30
    # 3   200719   61226  2016-01-31 23:59:08       0.0     6     8     30
    # 4   263587   72348  2016-01-31 23:59:08       NaN     1     5    159
    ########## Begin ##########
    data['time'] = pd.to_datetime(data['time'])  # 转换时间格式为datetime类型
    data = data[(data['time'] >= '2016-02-01') & (data['type'] == 6)]
    ########## End  ##########
    return data

def sample_data(data):
    # 使用pd.DataFrame.sample函数进行随机抽样，不放回的随机抽取5000个样本，
    # 数据结构如下：
    #    user_id  sku_id                 time  model_id  type  cate  brand
    # 0   266079  138778  2016-01-31 23:59:02       NaN     1     8    403
    # 1   266079  138778  2016-01-31 23:59:03       0.0     6     8    403
    # 2   200719   61226  2016-01-31 23:59:07       NaN     1     8     30
    # 3   200719   61226  2016-01-31 23:59:08       0.0     6     8     30
    # 4   263587   72348  2016-01-31 23:59:08       NaN     1     5    159
    ########## Begin ##########
    data = data.sample(n=5000, replace=False)
    ########## End  ##########
    return data

def clear_data(df):
    # 根据提示补全下列操作，请在已有的代码上添加操作，
    # 不要改动原有的变量名，案例数据结构如下：
    #        col1      col2      col3      col4
    # 0 -1.055712 -0.196175 -0.813023 -0.806857
    # 1  0.972878       NaN -1.722135 -0.638893
    # 2  0.444641 -0.189607 -0.199307  3.496211
    # 3  0.273065 -1.970887  0.954170  0.823823
    # 4  0.729248 -1.036644  1.398436       NaN
    # 5 -0.323439  0.208351 -0.429920 -0.175628
    ########## Begin ##########
    nan_result_pd1 = df.dropna()
    ########## End  ##########
    return nan_result_pd1

代码#合并训练数据和测试数据 datal = pd.concat([data_train ,data_test],axis =0) #处理 data _ received 属性、 date 属性 data1['date_received ']=data1['date_received'].astype('str'). apply ( lambda x : x . split ('.')[0]) datal [' date_received ']= pd . to_datetime (data1[' date_received ']) datal [' date ']= datal (' date '). astype (' str '). apply ( lambda x : x . split ('.')[0]) datal [' date ']= pd . to_datetime ( datal [' date '])报错name 'data1' is not defined解决

在代码中，第二行中的`data1`没有被定义，因此会报错。可以将第二行的`data1`改为`datal`，因为上一行已经定义了`datal`作为合并后的数据集。修改后的代码如下：

# 合并训练数据和测试数据
datal = pd.concat([data_train, data_test], axis=0)

# 处理 data_received 属性、date属性
datal['date_received'] = datal['date_received'].astype('str').apply(
    lambda x: x.split('.')[0])
datal['date_received'] = pd.to_datetime(datal['date_received'])

datal['date'] = datal['date'].astype('str').apply(
    lambda x: x.split('.')[0])
datal['date'] = pd.to_datetime(datal['date'])