Find value from row , above and below using If statements in python - Stack Overflow

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import pandas as pd
import numpy as np
df= pd.read_csv ("file.csv")
n = 0

a = 7        # 1st value to find in row1
b = 39       # 2nd value to find in row2
c = 10       # 3rd value to find in row3
d = 38       # 4th value to find in row4

value_1 = 5
value_2 = 21

while n < len(df)-1 : 
    if df.loc[n].isin([a]).any                    # 7 is in any in n row
        if df.loc[n+1].isin([b]).any():           #39 is in any in n+1 row
            if df.loc[n+2].isin([c]).any():       #10 is in any in n+2 row
                if df.loc[n+3].isin([d]).any():   #44 is in any in n+3 row

                        if df.loc[n].isin([value_1]).any():       
                             if (df.loc[n].isin([value_2 ]).any() or df.loc[n-1].isin([value_2 ]).any() or df.loc[n+1].isin([value_2 ]).any()):                                                                     
                                  display (df.loc[n:n])
                        elif df.loc[n+1].isin([value_1]).any() :     
                            if (df.loc[n+1].isin([value_2 ]).any() or df.loc[n].isin([value_2 ]).any() or df.loc[n+1].isin([value_2 ]).any()): 
                               display (df.loc[n:n])
                        elif df.loc[n-1].isin([value_1]).any() :
                            if (df.loc[n-1].isin([value_2 ]).any() or df.loc[n-2].isin([value_2 ]).any() or df.loc[n].isin([value_2 ]).any()): 
                                  display (df.loc[n:n])

I am very beginner in python. Sorry for the mess. I am trying to find a,b,c,d to find in row 1,2,3,4 from data and once it matches from the data , then if value_1 be in row n and value_2 is in row n or n-1 or n+1 if (df.loc[n].isin([value_2 ]).any() or df.loc[n-1].isin([value_2 ]).any() or df.loc[n+1].isin([value_2 ]).any()): then show the data. and then same again one below and one above. The code is running but not finding all the matched datas but few. Have i done any mistake using or operator?

For example, first it will find the value a(7) from any row, (here in found in row 4) once it found then more to next row to find b (39 found in row 5), and then c(10 found in row 6) and d(38 found in row 7). Once it found, then it will search for value_1 (5) in the row of a(7 which was found in row 4) or one above(row 3) or below (row 5)

     A   B   C   D   E   F  
1 | 4   5   8   16  5   44  #VALUE_1 (5)
2 | 1   4   12  15  22  21  #VALUE_2 (21)
3 | 2   11  13  15  28  33  
4 | 5   15  29  35  7   33
5 | 6   7   39  12  14  16  
6 | 1   9   10  12  20  26  
7 | 6   38  20  36  33  34  
8 | 12  21  7   28  35  39  
9 | 5   18  39  33  35  36  
10| 4   7   10  18  19  28  
11| 3   4   15  19  28  38  

and later when value_1 (5) is found, then it search for value_2 (21) on the row of value_1 (which was found in row 4) or one above (row 3) or below (row 5). if found then, it will print the row 1, and continue to find more match

import pandas as pd
import numpy as np
df= pd.read_csv ("file.csv")
n = 0

a = 7        # 1st value to find in row1
b = 39       # 2nd value to find in row2
c = 10       # 3rd value to find in row3
d = 38       # 4th value to find in row4

value_1 = 5
value_2 = 21

while n < len(df)-1 : 
    if df.loc[n].isin([a]).any                    # 7 is in any in n row
        if df.loc[n+1].isin([b]).any():           #39 is in any in n+1 row
            if df.loc[n+2].isin([c]).any():       #10 is in any in n+2 row
                if df.loc[n+3].isin([d]).any():   #44 is in any in n+3 row

                        if df.loc[n].isin([value_1]).any():       
                             if (df.loc[n].isin([value_2 ]).any() or df.loc[n-1].isin([value_2 ]).any() or df.loc[n+1].isin([value_2 ]).any()):                                                                     
                                  display (df.loc[n:n])
                        elif df.loc[n+1].isin([value_1]).any() :     
                            if (df.loc[n+1].isin([value_2 ]).any() or df.loc[n].isin([value_2 ]).any() or df.loc[n+1].isin([value_2 ]).any()): 
                               display (df.loc[n:n])
                        elif df.loc[n-1].isin([value_1]).any() :
                            if (df.loc[n-1].isin([value_2 ]).any() or df.loc[n-2].isin([value_2 ]).any() or df.loc[n].isin([value_2 ]).any()): 
                                  display (df.loc[n:n])

I am very beginner in python. Sorry for the mess. I am trying to find a,b,c,d to find in row 1,2,3,4 from data and once it matches from the data , then if value_1 be in row n and value_2 is in row n or n-1 or n+1 if (df.loc[n].isin([value_2 ]).any() or df.loc[n-1].isin([value_2 ]).any() or df.loc[n+1].isin([value_2 ]).any()): then show the data. and then same again one below and one above. The code is running but not finding all the matched datas but few. Have i done any mistake using or operator?

For example, first it will find the value a(7) from any row, (here in found in row 4) once it found then more to next row to find b (39 found in row 5), and then c(10 found in row 6) and d(38 found in row 7). Once it found, then it will search for value_1 (5) in the row of a(7 which was found in row 4) or one above(row 3) or below (row 5)

     A   B   C   D   E   F  
1 | 4   5   8   16  5   44  #VALUE_1 (5)
2 | 1   4   12  15  22  21  #VALUE_2 (21)
3 | 2   11  13  15  28  33  
4 | 5   15  29  35  7   33
5 | 6   7   39  12  14  16  
6 | 1   9   10  12  20  26  
7 | 6   38  20  36  33  34  
8 | 12  21  7   28  35  39  
9 | 5   18  39  33  35  36  
10| 4   7   10  18  19  28  
11| 3   4   15  19  28  38  

and later when value_1 (5) is found, then it search for value_2 (21) on the row of value_1 (which was found in row 4) or one above (row 3) or below (row 5). if found then, it will print the row 1, and continue to find more match

• python
• if-statement

Share Improve this question Follow edited Feb 17 at 10:46 Kan asked Feb 16 at 16:06 KanKan 1544 bronze badges 2

• Please provide a minimum example which shows the output required from defined input data (see minimal reproducible example). The code you provide will not run and the logic is not clear. – user19077881 Commented Feb 16 at 18:29
• suggest this question is closed and the OP encouraged write down WHAT they are attempting (perhaps in pseudocode), removing the code they've written. – ticktalk Commented Feb 17 at 12:53

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1 Answer 1

Sorted by: Reset to default 1

I'm not sure I understood your question completely correctly, but here is one way to accomplish the task:

import pandas as pd

    df = pd.read_csv("file.csv", delimiter=',')
    
    a = 7  # 1st value
    b = 39  # 2nd value
    c = 10  # 3rd value
    d = 38  # 4th value
    
    value_1 = 5
    value_2 = 21
    
    for i, row in df.iterrows():
        if (i < len(df) - 3 and  # checks if there are 3 more lines after
                a in row.unique() and  # checks a in current line
                b in df.loc[i + 1].unique() and  # checks b in line with index [i + 1]
                c in df.loc[i + 2].unique() and  # checks c in line with index [i + 2]
                d in df.loc[i + 3].unique()):  # checks d in line with index [i + 3]
    
            for j in range(i - 1, i + 2):  # check is value_1 in rows [i - 1], [i], [i + 1]
                if value_1 in df.loc[j].unique():
    
                    for k in range(j - 1, j + 2):  # check is value_2 in rows [j - 1], [j], [j + 1]
                        if value_2 in df.loc[k].unique():

                            print(row)

I left explanations of the code in the comments.

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