TypeError：“NoneType”和“float”的实例之间不支持“<”答案

【问题标题】：TypeError: '<' not supported between instances of 'NoneType' and 'float'TypeError：“NoneType”和“float”的实例之间不支持“<”
【发布时间】：2021-03-18 08:05:40
【问题描述】：

我正在关注 YouTube 教程，并且我根据教程编写了这段代码

import numpy as np
import pandas as pd
from scipy.stats import percentileofscore as score

my_columns = [
  'Ticker', 
  'Price', 
  'Number of Shares to Buy', 
  'One-Year Price Return',
  'One-Year Percentile Return',
  'Six-Month Price Return',
  'Six-Month Percentile Return',
  'Three-Month Price Return',
  'Three-Month Percentile Return',
  'One-Month Price Return',
  'One-Month Percentile Return'
  ]
final_df = pd.DataFrame(columns = my_columns)
# populate final_df here....
pd.set_option('display.max_columns', None)
print(final_df[:1])
time_periods = ['One-Year', 'Six-Month', 'Three-Month', 'One-Month']    
for row in final_df.index:
  for time_period in time_periods:
    change_col = f'{time_period} Price Return'
    print(type(final_df[change_col])) 
    percentile_col = f'{time_period} Percentile Return'
    print(final_df.loc[row, change_col])
    final_df.loc[row, percentile_col] = score(final_df[change_col], final_df.loc[row, change_col])
print(final_df)

它将我的数据框打印为

| Ticker |  Price  | Number of Shares to Buy | One-Year Price Return  | One-Year Percentile Return | Six-Month Price Return | Six-Month Percentile Return | Three-Month Price Return | Three-Month Percentile Return | One-Month Price Return  | One-Month Percentile Return  |
|--------|---------|-------------------------|------------------------|----------------------------|------------------------|-----------------------------|--------------------------|-------------------------------|-------------------------|------------------------------|
| A      |  120.38 | N/A                     | 0.437579               | N/A                        | 0.280969               | N/A                         | 0.198355                 | N/A                           | 0.0455988               |             N/A              |

但是当我调用 score 函数时，我得到了这个错误

<class 'pandas.core.series.Series'>
0.4320217937551543
Traceback (most recent call last):
  File "program.py", line 72, in <module>
    final_df.loc[row, percentile_col] = score(final_df[change_col], final_df.loc[row, change_col])
  File "/Users/abhisheksrivastava/Library/Python/3.7/lib/python/site-packages/scipy/stats/stats.py", line 2017, in percentileofscore
    left = np.count_nonzero(a < score)
TypeError: '<' not supported between instances of 'NoneType' and 'float'

出了什么问题？我在 YouTube 视频中看到了相同的代码。我几乎没有使用 Python 的经验

编辑：

我也试过

print(type(final_df['One-Year Price Return'])) 
print(type(final_df['Six-Month Price Return'])) 
print(type(final_df['Three-Month Price Return'])) 
print(type(final_df['One-Month Price Return'])) 
for row in final_df.index:
  final_df.loc[row, 'One-Year Percentile Return'] = score(final_df['One-Year Price Return'], final_df.loc[row, 'One-Year Price Return'])
  final_df.loc[row, 'Six-Month Percentile Return'] = score(final_df['Six-Month Price Return'], final_df.loc[row, 'Six-Month Price Return'])
  final_df.loc[row, 'Three-Month Percentile Return'] = score(final_df['Three-Month Price Return'], final_df.loc[row, 'Three-Month Price Return'])
  final_df.loc[row, 'One-Month Percentile Return'] = score(final_df['One-Month Price Return'], final_df.loc[row, 'One-Month Price Return'])
print(final_df)

但还是出现同样的错误

<class 'pandas.core.series.Series'>
<class 'pandas.core.series.Series'>
<class 'pandas.core.series.Series'>
<class 'pandas.core.series.Series'>
<class 'pandas.core.series.Series'>
Traceback (most recent call last):
  File "program.py", line 71, in <module>
    final_df.loc[row, 'One-Year Percentile Return'] = score(final_df['One-Year Price Return'], final_df.loc[row, 'OneYear Price Return'])
  File "/Users/abhisheksrivastava/Library/Python/3.7/lib/python/site-packages/scipy/stats/stats.py", line 2017, in percentileofscore
    left = np.count_nonzero(a < score)
TypeError: '<' not supported between instances of 'NoneType' and 'float'

【问题讨论】：

final_df 中的一个列名最后必须有多余的空格。因此，当您尝试使用 final_df[change_col] 访问该列时，您的数据框无法找到该列。所以它返回 None 而不是 pandas 系列。您可以输入 print(type(final_df[change_col])) 并在此处复制结果吗？它将更加清晰。
我更改了代码并添加了打印语句。类型是<class 'pandas.core.series.Series'>
请注意，您的最后一条错误消息是指“OneYear”而不是“One-Year”。我的猜测是您发布的代码并不是您正在运行的代码。
它的One-Year 无处不在。抱歉，我正在尝试删除 -

标签： python pandas

【解决方案1】：

@Taras Mogetich 写的非常正确，但是您可能需要将 if 语句放在它自己的 for 循环中。 Liko so：

for row in hqm_dataframe.index:
    for time_period in time_periods:
    
        change_col = f'{time_period} Price Return'
        percentile_col = f'{time_period} Return Percentile'
        if hqm_dataframe.loc[row, change_col] == None:
            hqm_dataframe.loc[row, change_col] = 0.0

然后分别：

for row in hqm_dataframe.index:
    for time_period in time_periods:
    
        change_col = f'{time_period} Price Return'
        percentile_col = f'{time_period} Return Percentile'

        hqm_dataframe.loc[row, percentile_col] = score(hqm_dataframe[change_col], hqm_dataframe.loc[row, change_col])

【讨论】：

【解决方案2】：

我也在学习本教程。我深入研究了四个“___价格回报”列中的数据。查看我的批处理 API 调用，有四行的值为“None”而不是浮点数，这就是出现“NoneError”的原因，因为 percentileofscore 函数试图使用不是浮点数的“None”计算百分位数.

为了解决这个 API 错误，我手动将计算百分位数的 None 值更改为 0，代码如下...

time_periods = [
                'One-Year',
                'Six-Month',
                'Three-Month',
                'One-Month'
                ]

for row in hqm_dataframe.index:
    for time_period in time_periods:
        if hqm_dataframe.loc[row, f'{time_period} Price Return'] == None:
            hqm_dataframe.loc[row, f'{time_period} Price Return'] = 0

【讨论】：

【解决方案3】：

谷歌搜索我遇到的问题很有趣，这与您正在学习的教程完全相同！

如前所述，来自 API 调用的某些数据的值为 None，这会导致 percentileofscore 函数出错。我的解决方案是在初始创建 hqm_dataframe 时将所有 None 类型转换为整数 0。

hqm_columns = [
    'Ticker',
    'Price',
    'Number of Shares to Buy',
    'One-Year Price Return',
    'One-Year Return Percentile',
    'Six-Month Price Return',
    'Six-Month Return Percentile',
    'Three-Month Price Return',
    'Three-Month Return Percentile',
    'One-Month Price Return',
    'One-Month Return Percentile'
]

hqm_dataframe = pd.DataFrame(columns=hqm_columns)
convert_none = lambda x : 0 if x is None else x

for symbol_string in symbol_strings:
    batch_api_call_url = f'https://sandbox.iexapis.com/stable/stock/market/batch?symbols={symbol_string}&types=price,stats&token={IEX_CLOUD_API_TOKEN}'
    data = requests.get(batch_api_call_url).json()
    
    for symbol in symbol_string.split(','):
        hqm_dataframe = hqm_dataframe.append(
            pd.Series(
                [
                    symbol,
                    data[symbol]['price'],
                    'N/A',
                    convert_none(data[symbol]['stats']['year1ChangePercent']),
                    'N/A',
                    convert_none(data[symbol]['stats']['month6ChangePercent']),
                    'N/A',
                    convert_none(data[symbol]['stats']['month3ChangePercent']),
                    'N/A',
                    convert_none(data[symbol]['stats']['month1ChangePercent']),
                    'N/A'
                ],
                index = hqm_columns
            ),
            ignore_index=True
        )

【讨论】：

【解决方案4】：

如下所示，只需将 None 值替换为 0，

hqm_dataframe.fillna(0,inplace=True)

【讨论】：

【解决方案5】：

填充final_df后，也可以这样做：

final_df.fillna(value=0, inplace=True)

如果您只想将每个 NaN 替换为 0。

【讨论】：

【解决方案6】：

您确定这是整个代码吗？在我的情况下，它返回空数据框。请提供更多详细信息

【讨论】：

对 Web 服务的调用很长，并没有真正增加多少价值。我已经提供了返回到上面数据框中的数据。
为了给您合适的答案，了解 DataFrame 内部的内容很重要。问题在于得分函数。我需要知道哪些值是 None 以及何时

【解决方案7】：

大多数其他回复都是正确的，问题是数据框中没有值，并且 scipy stats 的 percentileofscore 方法不知道如何解析这些值。我有一个不同的解决方案，它不涉及解析数据帧上的每个条目。

我使用数据框的 .replace 方法将所有 None 条目替换为 0。inplace = True 在那里，以便将更改保存到数据框，而不必分配它。

hqm_dataframe.replace([None], 0, inplace = True)

【讨论】：

【解决方案8】：

使用 np.nan 代替 'N/A' 并将浮点类型设置为列。

final_df = pd.DataFrame(columns = my_columns)

for symbol_string in symbol_strings:
    batch_api_call_url = f'https://sandbox.iexapis.com/stable/stock/market/batch?symbols={symbol_string}&types=price,stats&token={IEX_CLOUD_API_TOKEN}'
    data = requests.get(batch_api_call_url).json()
#    print(symbol_string.split(','))
#    print(data['AAPL']['stats'])
    for symbol in symbol_string.split(','):
        final_df = final_df.append(
            pd.Series(
                [
                    symbol,
                    data[symbol]['price'],
                    data[symbol]['stats']['year1ChangePercent'],
                    np.nan
                ],
                index = my_columns
            ),
            ignore_index=True
        )

hqm_df = pd.DataFrame(columns = hqm_columns)

for symbol_string in symbol_strings:
    batch_api_call_url = f'https://sandbox.iexapis.com/stable/stock/market/batch?symbols={symbol_string}&types=price,stats&token={IEX_CLOUD_API_TOKEN}'
    data = requests.get(batch_api_call_url).json()
    for symbol in symbol_string.split(','):
        hqm_df = hqm_df.append(
            pd.Series(
                [
                    symbol,
                    data[symbol]['price'],
                    np.nan,
                    data[symbol]['stats']['year1ChangePercent'],
                    np.nan,
                    data[symbol]['stats']['month6ChangePercent'],
                    np.nan,
                    data[symbol]['stats']['month3ChangePercent'],
                    np.nan,
                    data[symbol]['stats']['month1ChangePercent'],
                    np.nan
                ],
                index = hqm_columns
            ),
            ignore_index=True
        )

hqm_df['One-Year Price Return'] = hqm_df['One-Year Price Return'].astype('float')
hqm_df['Six-Month Price Return'] = hqm_df['Six-Month Price Return'].astype('float')
hqm_df['Three-Month Price Return'] = hqm_df['Three-Month Price Return'].astype('float')
hqm_df['One-Month Price Return'] = hqm_df['One-Month Price Return'].astype('float')

【讨论】：