KeyError: 'date'错误求助——COVID-19数据季度可视化问题

问题背景 #

我正在用COVID-19数据集绘制疫情概览图表，尝试按季度分组计算每百万总病例数并用Seaborn可视化，但运行代码时触发KeyError: 'date'。奇怪的是date列并未缺失，且之前用该列实现的每日死亡数统计代码能正常运行，需要找出错误原因并解决。

出错代码 #

# Convert date column to datetime type
df['date'] = pd.to_datetime(df.date)

# Group data by quarter and calculate total cases per million
df_total_cases_quarterly = df.groupby(df['date'].dt.quarter).agg({'total_cases_per_million': 'sum'}).reset_index()

# Create bar plot for total cases per million on a quarterly basis
sns.set_style('whitegrid')
sns.barplot(x ='date', y = 'total_cases_per_million', data = df_total_cases_quarterly)
plt.title('Total Cases per Million (Worldwide) - Quarterly')
plt.xlabel('Quarter')
plt.ylabel('Total Cases per Million')
plt.xticks(ticks=[0, 1, 2, 3], labels=['Q1', 'Q2', 'Q3', 'Q4'])  # Update x-axis labels to show quarters
plt.show()

错误信息 #

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
/opt/anaconda3/lib/python3.9/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
   3628             try:
-> 3629                 return self._engine.get_loc(casted_key)
   3630             except KeyError as err:

/opt/anaconda3/lib/python3.9/site-packages/pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

/opt/anaconda3/lib/python3.9/site-packages/pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

KeyError: 'date'

The above exception was the direct cause of the following exception:

KeyError                                  Traceback (most recent call last)
/var/folders/rf/8yc43r0d13l2gw8m9r17pc7h0000gn/T/ipykernel_942/1110610808.py in <module>
      3 
      4 # Group data by quarter and calculate total cases per million
----> 5 df_total_cases_quarterly = df.groupby(df['date'].dt.quarter).agg({'total_cases_per_million': 'sum'}).reset_index() # df['date'].dt.quarter
      6 
      7 # Create bar plot for total cases per million on a quarterly basis

/opt/anaconda3/lib/python3.9/site-packages/pandas/core/frame.py in __getitem__(self, key)
   3503             if self.columns.nlevels > 1:
   3504                 return self._getitem_multilevel(key)
-> 3505             indexer = self.columns.get_loc(key)
   3506             if is_integer(indexer):
   3507                 indexer = [indexer]

/opt/anaconda3/lib/python3.9/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
   3629                 return self._engine.get_loc(casted_key)
   3630             except KeyError as err:
-> 3631                 raise KeyError(key) from err
   3632             except TypeError:
   3633                 # If we have a listlike key, _check_indexing_error will raise

KeyError: 'date'

可正常运行的参考代码 #

# Filter data for daily new deaths per million
df_daily_new_deaths = df.groupby('date').agg({'new_deaths_per_million': 'sum'}).reset_index()

# Create line plot for daily new deaths per million
sns.set_style('whitegrid')
sns.lineplot(x = 'date', y = 'new_deaths_per_million', data = df_daily_new_deaths)
plt.title('Daily New Deaths per Million (Worldwide)')
plt.xlabel('Date')
plt.ylabel('Daily New Deaths per Million')
plt.xticks(rotation = 45)
plt.show()

原因分析与解决方案 #

错误原因 #

报错的核心是当前代码中的df变量已经丢失了date列。虽然你之前的代码能正常运行，但很可能在两段代码的执行过程中，df被意外修改了（比如被重新赋值为其他数据集、执行了删除列的操作），导致调用df['date']时找不到该列。

解决方案 #

1. 检查当前df的结构
   先执行以下代码确认df的列情况：

   print(df.columns.tolist())
   

   如果输出里没有date，说明df已经被修改，需要重新加载原始数据集。

2. 重新加载原始数据（关键修复）
   在运行季度统计代码前，确保使用的是完整的原始数据集，不要复用之前操作后被修改的df。比如重新执行数据加载代码：

   # 示例：重新加载数据，根据你的实际加载方式调整
   import pandas as pd
   df = pd.read_csv('your_covid_dataset.csv')
   df['date'] = pd.to_datetime(df['date'])
   

3. 优化分组代码（避免后续问题）
   可以先给数据集添加明确的quarter列，再按该列分组，代码更清晰且不易出错：

   # 添加季度列
   df['quarter'] = df['date'].dt.quarter
   
   # 按季度分组计算
   df_total_cases_quarterly = df.groupby('quarter', as_index=False).agg(
       total_cases_per_million=('total_cases_per_million', 'sum')
   )
   
   # 绘图时使用quarter列作为x轴
   sns.set_style('whitegrid')
   sns.barplot(x='quarter', y='total_cases_per_million', data=df_total_cases_quarterly)
   plt.title('Total Cases per Million (Worldwide) - Quarterly')
   plt.xlabel('Quarter')
   plt.ylabel('Total Cases per Million')
   plt.xticks(ticks=[0, 1, 2, 3], labels=['Q1', 'Q2', 'Q3', 'Q4'])
   plt.show()
   

内容的提问来源于stack exchange，提问作者Taiwo Feyijimi