Index is in datetime64[ns] but still get TypeError: Only valid with DatetimeIndex
Index is in datetime64[ns] but still get TypeError: Only valid with DatetimeIndex
我正在尝试聚合每天 15 分钟时间间隔的数据。当我检查索引的数据类型时,它位于 datetime64[ns]
完成者:
df['timestamp'] = pd.to_datetime(df['timestamp'])
liquidation_1d_df = df.set_index('timestamp')
print(liquidation_1d_df.index.dtype)
但是,我仍然得到错误:
TypeError: Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, but got an instance of 'Index'
我运行以下代码进行聚合:
liquidation_1d_df.groupby([pd.Grouper(key='timestamp', freq='D'), 'exchange', 'side']).agg(total_liq = ('amount', 'sum'), avg_liq = ('amount', 'mean'))
有人知道出了什么问题以及如何解决吗?
而不是:
liquidation_1d_df = df.set_index('timestamp')
尝试:
df.set_index('timestamp',inplace=True)
print(df.index.dtype)
或者不想改变原来的df
liquidation_1d_df = df
liquidation_1d_df.set_index('timestamp',inplace=True)
print(liquidation_1d_df.index.dtype)
我正在尝试聚合每天 15 分钟时间间隔的数据。当我检查索引的数据类型时,它位于 datetime64[ns]
完成者:
df['timestamp'] = pd.to_datetime(df['timestamp'])
liquidation_1d_df = df.set_index('timestamp')
print(liquidation_1d_df.index.dtype)
但是,我仍然得到错误:
TypeError: Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, but got an instance of 'Index'
我运行以下代码进行聚合:
liquidation_1d_df.groupby([pd.Grouper(key='timestamp', freq='D'), 'exchange', 'side']).agg(total_liq = ('amount', 'sum'), avg_liq = ('amount', 'mean'))
有人知道出了什么问题以及如何解决吗?
而不是:
liquidation_1d_df = df.set_index('timestamp')
尝试:
df.set_index('timestamp',inplace=True)
print(df.index.dtype)
或者不想改变原来的df
liquidation_1d_df = df
liquidation_1d_df.set_index('timestamp',inplace=True)
print(liquidation_1d_df.index.dtype)