Oct-11-2020, 02:25 PM
Hi,
I have data frame as below:
group subgroup category name T S P R
A1 W 1 MAK 2 5.1 2 6
A1 L 2 RAL 2 5 2 8
C1 L 2 GAH 2 6 1.2 6
C1 W 1 JKA 2 5 2 6
S5 W 1 NMP 2 5 2 6
S5 W 2 NMP 2 5 2 6
C1 W 2 AAA 2 5 2 6
A1 W 2 TTY 2 5.1 2 4
Spec_df:
group subgroup category T S P R
A1 W 1 1.2 4.3 2.6 6
A1 L 2 2 2.3 2 6
C1 L 2 2 6 1.2 6
C1 W 1 2 5 2 6
S5 W 1 1.5 5 2 6
S5 W 2 2 5 2 6
C1 W 2 2 5 2 6
A1 W 2 0.3 3.6 1.3 4
I want to check the spec for each "T, S,P" column based on group, subgroup, category. Any fast way to do this? I did this using df.iterrows, and separte each condition based on group, subgroup, category, which is become too big loop.
if value in df > spec in spec_df, then mark as 1, else 0 for (T_F, S_F, P_F)
for example:
group subgroup category name T_F S _F P_F R
A1 W 1 MAK 1 0 0 6
A1 L 2 RAL 0 0 0 8
I have data frame as below:
group subgroup category name T S P R
A1 W 1 MAK 2 5.1 2 6
A1 L 2 RAL 2 5 2 8
C1 L 2 GAH 2 6 1.2 6
C1 W 1 JKA 2 5 2 6
S5 W 1 NMP 2 5 2 6
S5 W 2 NMP 2 5 2 6
C1 W 2 AAA 2 5 2 6
A1 W 2 TTY 2 5.1 2 4
Spec_df:
group subgroup category T S P R
A1 W 1 1.2 4.3 2.6 6
A1 L 2 2 2.3 2 6
C1 L 2 2 6 1.2 6
C1 W 1 2 5 2 6
S5 W 1 1.5 5 2 6
S5 W 2 2 5 2 6
C1 W 2 2 5 2 6
A1 W 2 0.3 3.6 1.3 4
I want to check the spec for each "T, S,P" column based on group, subgroup, category. Any fast way to do this? I did this using df.iterrows, and separte each condition based on group, subgroup, category, which is become too big loop.
if value in df > spec in spec_df, then mark as 1, else 0 for (T_F, S_F, P_F)
for example:
group subgroup category name T_F S _F P_F R
A1 W 1 MAK 1 0 0 6
A1 L 2 RAL 0 0 0 8