我正在尝试执行以下代码:
data = pd.read_csv('statistic.csv', parse_dates=True, index_col=['DATE'],
low_memory=False, nrows=5000000)
data_extracted = data.groupby(['DATE','ARTICLENO'])['QUANTITY'].sum().unstack()
data_extracted = data_extracted.loc['2015-01-01' : '2015-12-31']
data_extracted = data_extracted.replace([np.inf, -np.inf],
np.nan).fillna(0.0001)
data_pct_change = data_extracted.pct_change(axis=0).replace([np.inf, -
np.inf], np.nan).fillna(0)
data_pct_change.drop([col for col, val in data_pct_change.sum() if val == 0
], axis=1, inplace=True)
当我执行此操作时,我收到 TypeError: unsupported operand type(s) for/: 'str' and 'str'。
当我尝试执行 data_extracted['ARTICLENO] = data_extracted['ARTICLENO'].astype(float)
时,我收到相同的错误。
当我打印 data_extracted.dtypes 时,它都是 float 。
有人可以帮助我吗?
最佳答案
我认为需要将非数值转换为 NaN
s:
data_extracted['ARTICLENO'] = pd.to_numeric(data_extracted['ARTICLENO'], errors='coerce')
关于python - Pandas pct_change 不支持的操作数/对于 str 和 float,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/51534288/