类型错误：无法转换为数字

Question

这是我的代码：

file_path = 'TEST3.csv'  # Update the path to your CSV file
columns = ['Year','T', 'TM', 'Tm', 'PP', 'Yields_Blé_dur']
n_steps_in, n_steps_out = 3, 1
test_set_years = 5


df = load_data(file_path)

# Preprocess the data
df_processed = preprocess_data_columns(df, columns)
# Extract 'Year' for plotting purposes
years = df_processed['Year'].values

[这是我的数据库]()

GitHub 链接：https://github.com/Moiz1500/LSTM-model

我收到此错误：

TypeError                                 Traceback (most recent call last)
Cell In[44], line 10
      7 df = load_data(file_path)
      9 # Preprocess the data
---> 10 df_processed = preprocess_data_columns(df, columns)
     11 # Extract 'Year' for plotting purposes
     12 years = df_processed['Year'].values

Cell In[33], line 2
      1 def preprocess_data_columns(df, columns):
----> 2     df = df[columns].fillna(df.mean())  #Fill NaN values with the mean of the column
      3     return df

File c:\Users\hemic\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\frame.py:11335, in DataFrame.mean(self, axis, skipna, numeric_only, **kwargs)
  11327 @doc(make_doc("mean", ndim=2))
  11328 def mean(
  11329     self,
   (...)
  11333     **kwargs,
  11334 ):
> 11335     result = super().mean(axis, skipna, numeric_only, **kwargs)
  11336     if isinstance(result, Series):
  11337         result = result.__finalize__(self, method="mean")
...
-> 1678     raise TypeError(f"Could not convert {x} to numeric")
   1679 try:
   1680     x = x.astype(np.complex128)

Type Error: Could not convert ['1/1/20121/2/20121/3/201212/31/2023'] to numeric.
Output is truncated. View as a scrollable element or open in a text editor. Adjust cell output settings...

我该如何修复这个错误？

我不知道如何将年份列转换为日期

Answer 1

我不知道如何将年份列转换为日期

您可以将

Year

列转换为日期时间，从而避免出现

pd.to_datetime

:

的错误

# assumes import pandas as pd
df['Year'] = pd.to_datetime(df['Year'])

在取平均值之前。