将列名与行值进行比较并获取其他行值
Compare column name with a row value and getting other row value
我有这样一个数据框:
request_created_at sponsor_tier is_active status cash_in 2019/10 ... 2021/07
0 2019/10 2019/10 2.0 True 1 8901.00 ...
1 2019/10 2019/10 2.0 True 2 7602.00 ...
我想将我的所有列与日期(例如“2019/10”)与我第一列的值进行比较,并检查状态是否 == 1 以及状态是否 == 1 我想将我的现金价值复制到列“2019/10”行
def check_status (row, data):
if (row.status == 1) & (row.request_created_at == data):
return row.total_cash_in
elif (row.status == 4) & (row.request_created_at == data):
return row.total_cash_in
elif (row.status == 7) & (row.request_created_at == data):
return row.total_cash_in
else:
return 0
然后
for data in array_datas:
df[data] = df.apply(lambda row: check_status(row,data), axis=1)
我有这样一个数据框:
request_created_at sponsor_tier is_active status cash_in 2019/10 ... 2021/07
0 2019/10 2019/10 2.0 True 1 8901.00 ...
1 2019/10 2019/10 2.0 True 2 7602.00 ...
我想将我的所有列与日期(例如“2019/10”)与我第一列的值进行比较,并检查状态是否 == 1 以及状态是否 == 1 我想将我的现金价值复制到列“2019/10”行
def check_status (row, data):
if (row.status == 1) & (row.request_created_at == data):
return row.total_cash_in
elif (row.status == 4) & (row.request_created_at == data):
return row.total_cash_in
elif (row.status == 7) & (row.request_created_at == data):
return row.total_cash_in
else:
return 0
然后
for data in array_datas:
df[data] = df.apply(lambda row: check_status(row,data), axis=1)