Python处理CSV时存在列却报KeyError：DGLoadForecast未找到

我正在使用一份CSV数据集，编写了以下Python代码，按"Date"字段分组，计算PVLoadForecast、DGLoadForecast等多列的最大值、最小值、平均值和标准差：

# 获取负载的最大值和最小值，用于约束条件
max_load_pv = data.groupby(["Date"])["PVLoadForecast"].max()
min_load_pv = data.groupby(["Date"])["PVLoadForecast"].min()
mean_load_pv = data.groupby(["Date"])["PVLoadForecast"].mean()
std_load_pv = data.groupby(["Date"])["PVLoadForecast"].std()
max_load_dg = data.groupby(["Date"])["DGLoadForecast"].max()
min_load_dg = data.groupby(["Date"])["DGLoadForecast"].min()
mean_load_dg = data.groupby(["Date"])["DGLoadForecast"].mean()
std_load_dg = data.groupby(["Date"])["DGLoadForecast"].std()
max_load_wind = data.groupby(["Date"])["WindLoadForecast"].max()
min_load_wind = data.groupby(["Date"])["WindLoadForecast"].min()
mean_load_dg = data.groupby(["Date"])["WindLoadForecast"].mean()
std_load_dg = data.groupby(["Date"])["WindLoadForecast"].std()
max_load_bes= data.groupby(["Date"])["BESLoadForecast"].max()
min_load_bes =  data.groupby(["Date"])["BESLoadForecast"].min()
mean_load_dg =  data.groupby(["Date"])["BESLoadForecast"].mean()
std_load_dg =  data.groupby(["Date"])["BESLoadForecast"].std()
max_load_zonal =  data.groupby(["Date"])["ZonalLoadForecast"].max()
min_load_zonal = data.groupby(["Date"])["ZonalLoadForecast"].min()
mean_load_dg = data.groupby(["Date"])["ZonalLoadForecast"].mean()
std_load_dg = data.groupby(["Date"])["ZonalLoadForecast"].std()

运行代码时触发KeyError，提示找不到'DGLoadForecast'列，但我确认该列确实存在，且代码无语法和逻辑问题：

calculateParametersOnedayAheadEachMonth(t, str(d), str(m), "2016")
文件""，第29行，位于calculateParametersOnedayAheadEachMonth函数中
max_load_dg = data.groupby(["Date"])["DGLoadForecast"].max()
文件"/usr/local/lib/python3.10/dist-packages/pandas/core/groupby/generic.py"，第1416行，位于__getitem__方法中
return super().getitem(key)
文件"/usr/local/lib/python3.10/dist-packages/pandas/core/base.py"，第248行，位于__getitem__方法中
raise KeyError(f"Column not found: {key}")
KeyError: '找不到列: DGLoadForecast'

内容的提问来源于stack exchange，提问作者Esra