熊猫数据帧附加警告信息

Question

我有个代码可以发出警告信息

FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  data = data.append(row, ignore_index=True)

问题1:我想知道如何在下面的代码中使用concat而不是附加。

import pandas as pd
from datetime import datetime
data = pd.DataFrame()
for i in range(30):
    value = datetime.now()
    value1 = i
    value2 = i + 20
    value3 = i - 10
    if value3 >= 15:
        row = pd.Series([value, value1, value2, value3])
        data = data.append(row, ignore_index=True)
        
data.columns = ['Time', 'Entry Price', 'Target', 'Stop Loss']

print(data)

问题2："If“条件值将在我的实际代码中更改。有时，它的预期结果将是空数据帧。

例：

    if value3 >= 20:
        row = pd.Series([value, value1, value2, value3])
        data = data.append(row, ignore_index=True)
        
data.columns = ['Time', 'Entry Price', 'Target', 'Stop Loss']

print(data)

这是抛出错误

  File "C:\Users\jayan\.conda\envs\TestEnvironment\lib\site-packages\pandas\core\internals\base.py", line 70, in _validate_set_axis
    raise ValueError(

ValueError: Length mismatch: Expected axis has 0 elements, new values have 4 elements

我尝试了下面的代码，但是输出不是预期的格式。

import pandas as pd
from datetime import datetime
data = pd.DataFrame()
for i in range(30):
    value = datetime.now()
    value1 = i
    value2 = i + 20
    value3 = i - 10
    if value3 >= 15:
        row = pd.DataFrame([value, value1, value2, value3])
        data = pd.concat([data, row])

print(data)

输出

runfile('C:/AlgoTrade/test/untitled0.py', wdir='C:/AlgoTrade/test')
                            0
0  2022-11-11 17:06:29.709333
1                          25
2                          45
3                          15
0  2022-11-11 17:06:29.709333
1                          26
2                          46
3                          16
0  2022-11-11 17:06:29.709333
1                          27
2                          47
3                          17
0  2022-11-11 17:06:29.710333
1                          28
2                          48
3                          18
0  2022-11-11 17:06:29.710333
1                          29
2                          49
3                          19

预期输出应采用以下格式，没有任何警告消息。

runfile('C:/AlgoTrade/test/untitled0.py', wdir='C:/AlgoTrade/test')
                        Time  Entry Price  Target  Stop Loss
0 2022-11-11 17:09:32.104801           25      45         15
1 2022-11-11 17:09:32.104801           26      46         16
2 2022-11-11 17:09:32.104801           27      47         17
3 2022-11-11 17:09:32.104801           28      48         18
4 2022-11-11 17:09:32.104801           29      49         19

Answer 1

维护九月清单并附上它们。

import pandas as pd
from datetime import datetime
l1=[]
l2=[]
l3=[]
l4=[]


data = pd.DataFrame()
for i in range(30):
    value = datetime.now()
    value1 = i
    value2 = i + 20
    value3 = i - 10
    if value3 >= 15:

        l1.append(value)
        l2.append(value1)
        l3.append(value2)
        l4.append(value3)
   
data = pd.DataFrame(
    {'Time': l1,
     'Entry Price': l2,
     'Target': l3,
     'Stop Loss':l4
    })


print(data)

输出#

                       Time  Entry Price  Target  Stop Loss
0 2022-11-11 17:47:32.846271           25      45         15
1 2022-11-11 17:47:32.846271           26      46         16
2 2022-11-11 17:47:32.846271           27      47         17
3 2022-11-11 17:47:32.846271           28      48         18
4 2022-11-11 17:47:32.846271           29      49         19