如何创建形状为 [244, 14] 的特征数据框,类似于使用 tqdm 的初始数据框?
How do I create a feature dataframe with shape of [244, 14], similar to that of the initial dataframe using tqdm?
下面是我试过的:
rows=[]
for _, row in tqdm(df.iterrows(),total=df.shape[0]):
row_data=dict(
week_of_year=row.date.week,
month=row.date.month,
NGTC=row.NGTC,
NGRRO=row.NGRRO,
CSP=row.CSP,
NGMP=row.NGMP,
NGPI=row.NGPI,
NGUSV=row.NGUSV,
HOSP=row.HOSP,
HDD=row.HDD,
CDD=row.CDD,
NGSP=row.NGSP,
pre_NGSP=row.pre_NGSP,
change_NGSP=row.change_NGSP)
rows.append(row_data)
我试过上面的代码后,发现我的features_df.shape
是[1,14]
,而不是[244,14]
。请问我该如何解决这个问题?
你在 rows.append(row_data)
处写错了缩进,它不在循环中,所以你只得到了行中的最后一行。
rows=[]
for _, row in tqdm(df.iterrows(),total=df.shape[0]):
row_data=dict(
week_of_year=row.date.week,
month=row.date.month,
NGTC=row.NGTC,
NGRRO=row.NGRRO,
CSP=row.CSP,
NGMP=row.NGMP,
NGPI=row.NGPI,
NGUSV=row.NGUSV,
HOSP=row.HOSP,
HDD=row.HDD,
CDD=row.CDD,
NGSP=row.NGSP,
pre_NGSP=row.pre_NGSP,
change_NGSP=row.change_NGSP)
rows.append(row_data).
下面是我试过的:
rows=[]
for _, row in tqdm(df.iterrows(),total=df.shape[0]):
row_data=dict(
week_of_year=row.date.week,
month=row.date.month,
NGTC=row.NGTC,
NGRRO=row.NGRRO,
CSP=row.CSP,
NGMP=row.NGMP,
NGPI=row.NGPI,
NGUSV=row.NGUSV,
HOSP=row.HOSP,
HDD=row.HDD,
CDD=row.CDD,
NGSP=row.NGSP,
pre_NGSP=row.pre_NGSP,
change_NGSP=row.change_NGSP)
rows.append(row_data)
我试过上面的代码后,发现我的features_df.shape
是[1,14]
,而不是[244,14]
。请问我该如何解决这个问题?
你在 rows.append(row_data)
处写错了缩进,它不在循环中,所以你只得到了行中的最后一行。
rows=[]
for _, row in tqdm(df.iterrows(),total=df.shape[0]):
row_data=dict(
week_of_year=row.date.week,
month=row.date.month,
NGTC=row.NGTC,
NGRRO=row.NGRRO,
CSP=row.CSP,
NGMP=row.NGMP,
NGPI=row.NGPI,
NGUSV=row.NGUSV,
HOSP=row.HOSP,
HDD=row.HDD,
CDD=row.CDD,
NGSP=row.NGSP,
pre_NGSP=row.pre_NGSP,
change_NGSP=row.change_NGSP)
rows.append(row_data).