CODEWITHSUNDEEP
pythonpython-3.xpandasdataframeif-statement
user13424992
user13424992

Reputation:

If statement in pandas - python

I have a dataframe like this:

TechId  Rating  Category LateNight  Weekend  Weekdays 
  001     5      Teacher      1         1       0
  002     4      Student      0         1       1
  003     3      Driver       1         0       1
  004     1      Teacher      1         0       1
  005     1      Student      1         1       0
  006     0      Teacher      1         1       1
  007     2      Teacher      0         0       1

I wanted to find if the Category = Teacher is available on Weekdays, that should display TechID 003,006 & 007 in the output.

I tried this code,

Category = int(input("Enter the Trade ID you want technicians in:"))
Latenight = int(input("Press 1 if you want technicians in Latenight/else press 0:"))
Weekends = int(input("Press 1 if you want technicians in Weekends/else press 0:"))
WeekDays = int(input("Press 1 if you want technicians in WeekDays/else press 0:"))

df2 = df1_new[(df1_new['Category'] == Category) &(df1_new['Weekends'] == Weekends) & (df1_new['LateNight'] == Latenight)]
df2 = df1_new[(df1_new['Category'] == Category) &(df1_new['WeekDays'] == WeekDays) & (df1_new['LateNight'] == Latenight)]
df2 = df1_new[(df1_new['Category'] == Category) &(df1_new['WeekDays'] == WeekDays) & (df1_new['LateNight'] == Latenight) & (df1_new['Weekends'] == Weekends)]
df2_new= df2.sort_values(by=['divcount'], ascending=False)
df2_new.head()

Enter the Category you want : Teacher      
Press 1 if you want technicians in Latenight/else press 0:0
Press 1 if you want technicians in Weekends/else press 0:0
Press 1 if you want technicians in WeekDays/else press 0:1

But this displays only TechID 007 row. Some TechID might be available on both Weekend & weekdays. That should also be considered. Can anyone help me out?

Upvotes: 0

Views: 58

Answers (3)

Vishal Upadhyay
Vishal Upadhyay

Reputation: 821

Try this:

Teachers available on Weekdays:

df2 = df.loc[(df['Category'] == 'Teacher') & (df['Weekdays'] == 1)]
df2

Output:

TechId  Rating  Category    LateNight   Weekend Weekdays
004         1   Teacher         1           0       1
006         0   Teacher         1           1       1
007         2   Teacher         0           0       1

Teachers available on Weekdays and LateNight:

df2 = df.loc[(df['Category'] == 'Teacher') & (df['Weekdays'] & df['LateNight']==1)]
df2

Output:

TechId  Rating  Category    LateNight   Weekend Weekdays
004         1   Teacher         1           0       1
006         0   Teacher         1           1       1

Upvotes: 0

Abhishek Verma
Abhishek Verma

Reputation: 1729

First of all, your answer will be 004, 006 and 007.

And a short way to do this, will be:

df1_new[(df1_new['Category'] == 'Teacher') & (df1_new['Weekdays'] == 1)]

Upvotes: 0

Serge Ballesta
Serge Ballesta

Reputation: 149185

The request should ignore the filter when the answer is 0 instead of asking for 0 values. A simple way would be to use isin([0,1]) for 0 and isin([1]) for 1:

Category = int(input("Enter the Trade ID you want technicians in:"))
Latenight = [1] if int(input("Press 1 if you want technicians in Latenight/else press 0:")) else [0,1]
Weekends =[1] if  int(input("Press 1 if you want technicians in Weekends/else press 0:")) else [0,1]
WeekDays = [1] if int(input("Press 1 if you want technicians in WeekDays/else press 0:")) else [0,1]

df2 = df1_new[(df1_new['Category'] == Category) &(df1_new['WeekDays'].isin(WeekDays)) & (df1_new['LateNight'].isin(Latenight)) & (df1_new['Weekends'].isin(Weekends))]

Upvotes: 2

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