Convert values in column from hex to binary in pandas data frame










2















I have one column in pandas data frame with hex values, for example:



Data
1A
2B
BB
FF
A7
78
CB


I want to convert hex values in binary, then from binary to take first 3 bits and finally convert 3 bits value in decimal.



Data column in binary will be:



Data
00011010
00101011
10111011
11111111
10100111
01111000
11001011


the first 3 bits:



Data
010
011
011
111
111
000
011


and finally the desired value in decimal:



Data
2
3
3
7
7
0
3


How to do this? I tried with bin() function, but it doesn't work with pandas data frames.










share|improve this question

















  • 1





    Can you share your work so that it ll be easy for us to replicate.

    – Naveen
    Nov 11 '18 at 21:12











  • I shared everything I could...I wish I could share more, but it is not allowed.

    – slobokv83
    Nov 12 '18 at 8:11















2















I have one column in pandas data frame with hex values, for example:



Data
1A
2B
BB
FF
A7
78
CB


I want to convert hex values in binary, then from binary to take first 3 bits and finally convert 3 bits value in decimal.



Data column in binary will be:



Data
00011010
00101011
10111011
11111111
10100111
01111000
11001011


the first 3 bits:



Data
010
011
011
111
111
000
011


and finally the desired value in decimal:



Data
2
3
3
7
7
0
3


How to do this? I tried with bin() function, but it doesn't work with pandas data frames.










share|improve this question

















  • 1





    Can you share your work so that it ll be easy for us to replicate.

    – Naveen
    Nov 11 '18 at 21:12











  • I shared everything I could...I wish I could share more, but it is not allowed.

    – slobokv83
    Nov 12 '18 at 8:11













2












2








2








I have one column in pandas data frame with hex values, for example:



Data
1A
2B
BB
FF
A7
78
CB


I want to convert hex values in binary, then from binary to take first 3 bits and finally convert 3 bits value in decimal.



Data column in binary will be:



Data
00011010
00101011
10111011
11111111
10100111
01111000
11001011


the first 3 bits:



Data
010
011
011
111
111
000
011


and finally the desired value in decimal:



Data
2
3
3
7
7
0
3


How to do this? I tried with bin() function, but it doesn't work with pandas data frames.










share|improve this question














I have one column in pandas data frame with hex values, for example:



Data
1A
2B
BB
FF
A7
78
CB


I want to convert hex values in binary, then from binary to take first 3 bits and finally convert 3 bits value in decimal.



Data column in binary will be:



Data
00011010
00101011
10111011
11111111
10100111
01111000
11001011


the first 3 bits:



Data
010
011
011
111
111
000
011


and finally the desired value in decimal:



Data
2
3
3
7
7
0
3


How to do this? I tried with bin() function, but it doesn't work with pandas data frames.







python pandas dataframe binary hex






share|improve this question













share|improve this question











share|improve this question




share|improve this question










asked Nov 11 '18 at 21:06









slobokv83slobokv83

729




729







  • 1





    Can you share your work so that it ll be easy for us to replicate.

    – Naveen
    Nov 11 '18 at 21:12











  • I shared everything I could...I wish I could share more, but it is not allowed.

    – slobokv83
    Nov 12 '18 at 8:11












  • 1





    Can you share your work so that it ll be easy for us to replicate.

    – Naveen
    Nov 11 '18 at 21:12











  • I shared everything I could...I wish I could share more, but it is not allowed.

    – slobokv83
    Nov 12 '18 at 8:11







1




1





Can you share your work so that it ll be easy for us to replicate.

– Naveen
Nov 11 '18 at 21:12





Can you share your work so that it ll be easy for us to replicate.

– Naveen
Nov 11 '18 at 21:12













I shared everything I could...I wish I could share more, but it is not allowed.

– slobokv83
Nov 12 '18 at 8:11





I shared everything I could...I wish I could share more, but it is not allowed.

– slobokv83
Nov 12 '18 at 8:11












2 Answers
2






active

oldest

votes


















3














We can do this by a chain of actions:



  1. first we convert the hexadecimal number to an int with .apply(int, base=16);

  2. next we convert this to binary data, with .apply(bin);

  3. next we chunk off the first two characters with .str[2:];

  4. then we obtain the last three characters with .str[-3:]; and

  5. finally we again interpret these as ints, with .apply(int, base=2).

So:



>>> df.Data.apply(int, base=16).apply(bin).str[2:].str[-3:].apply(int, base=2)
0 2
1 3
2 3
3 7
4 7
5 0
6 3
Name: Data, dtype: int64


We can however use another strategy here:



  1. we first convert the hexadecimal number to an int; and

  2. then we apply a bitwise and with 0b111.

for example:



>>> df.Data.apply(int, base=16) & 0b111
0 2
1 3
2 3
3 7
4 7
5 0
6 3
Name: Data, dtype: int64


The second attempt is not only simpler, but faster as well, approximately by 66%:



>>> timeit(first_strategy, number=10000)
6.962630775000434
>>> timeit(second_strategy, number=10000)
2.330652763019316


for a dataframe that repeats the sample data 100 times, we get:



>>> timeit(first_strategy, number=10000)
17.603060900000855
>>> timeit(second_strategy, number=10000)
5.901462858979357


this is again 66% faster.






share|improve this answer




















  • 1





    I like the other strategy... I might be tempted to use 0b111 instead of 7 (or possibly (1 << N) - 1 if it's going to be "the last N bits" where N is not just a couple ) or something but...

    – Jon Clements
    Nov 11 '18 at 21:18












  • @JonClements: thanks for the suggestion, edited.

    – Willem Van Onsem
    Nov 11 '18 at 21:26











  • Thank you very much. It works...but if I have to extract 3 bits from the 2nd to 5th position in a byte (for example, from "10010110" it is "010"), what I have to do? For the first solution, I could put str[p1:p2] and use None if it is the end of a string. But for the second solution, which by the way I like very much, how to extract bits that I want?

    – slobokv83
    Nov 12 '18 at 7:50











  • @slobokv83: you can first divide it by (1<<2) (so 4), like (df.Data.apply(int, base=16) // (1 << 2)) & 0b111

    – Willem Van Onsem
    Nov 12 '18 at 11:10






  • 1





    @slobokv83: well as said, you can use (df.Data.apply(int, base=16) // (1 << o)) & ((1 << w) - 1) to obtain the values between the bits o and o+w, no need to slice, zfill`, etc.

    – Willem Van Onsem
    Nov 12 '18 at 12:05


















2














You can use:



df.Data.apply(lambda v: int(format(int(v, 16), '08b')[-3:], 2))


Which gives you:



0 2
1 3
2 3
3 7
4 7
5 0
6 3
Name: Data, dtype: int64


Those steps are:



  • Take your original data and convert it to decimal using int(number, 16) (base 16 is hex) (int('1A', 16) == 26)

  • Take that number and format it as a binary string format(number, '08b') gives you an character string of 0/1's zero filled on the left (format(26, '08b') == '00011010')

  • Take the last 3 characters of that string [-3:] ('010') and convert it to decimal with a base 2, int(binary_string[-3:], 2) gives you: 2





share|improve this answer























  • Thank you very much. It works fine...I have another question - if I need for the length of the bits array to be variable, what I have to do? You put '08b', and if I want in some moment to be '16b', should I put like 'lengthb' and for length give some value?

    – slobokv83
    Nov 12 '18 at 7:58










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2 Answers
2






active

oldest

votes








2 Answers
2






active

oldest

votes









active

oldest

votes






active

oldest

votes









3














We can do this by a chain of actions:



  1. first we convert the hexadecimal number to an int with .apply(int, base=16);

  2. next we convert this to binary data, with .apply(bin);

  3. next we chunk off the first two characters with .str[2:];

  4. then we obtain the last three characters with .str[-3:]; and

  5. finally we again interpret these as ints, with .apply(int, base=2).

So:



>>> df.Data.apply(int, base=16).apply(bin).str[2:].str[-3:].apply(int, base=2)
0 2
1 3
2 3
3 7
4 7
5 0
6 3
Name: Data, dtype: int64


We can however use another strategy here:



  1. we first convert the hexadecimal number to an int; and

  2. then we apply a bitwise and with 0b111.

for example:



>>> df.Data.apply(int, base=16) & 0b111
0 2
1 3
2 3
3 7
4 7
5 0
6 3
Name: Data, dtype: int64


The second attempt is not only simpler, but faster as well, approximately by 66%:



>>> timeit(first_strategy, number=10000)
6.962630775000434
>>> timeit(second_strategy, number=10000)
2.330652763019316


for a dataframe that repeats the sample data 100 times, we get:



>>> timeit(first_strategy, number=10000)
17.603060900000855
>>> timeit(second_strategy, number=10000)
5.901462858979357


this is again 66% faster.






share|improve this answer




















  • 1





    I like the other strategy... I might be tempted to use 0b111 instead of 7 (or possibly (1 << N) - 1 if it's going to be "the last N bits" where N is not just a couple ) or something but...

    – Jon Clements
    Nov 11 '18 at 21:18












  • @JonClements: thanks for the suggestion, edited.

    – Willem Van Onsem
    Nov 11 '18 at 21:26











  • Thank you very much. It works...but if I have to extract 3 bits from the 2nd to 5th position in a byte (for example, from "10010110" it is "010"), what I have to do? For the first solution, I could put str[p1:p2] and use None if it is the end of a string. But for the second solution, which by the way I like very much, how to extract bits that I want?

    – slobokv83
    Nov 12 '18 at 7:50











  • @slobokv83: you can first divide it by (1<<2) (so 4), like (df.Data.apply(int, base=16) // (1 << 2)) & 0b111

    – Willem Van Onsem
    Nov 12 '18 at 11:10






  • 1





    @slobokv83: well as said, you can use (df.Data.apply(int, base=16) // (1 << o)) & ((1 << w) - 1) to obtain the values between the bits o and o+w, no need to slice, zfill`, etc.

    – Willem Van Onsem
    Nov 12 '18 at 12:05















3














We can do this by a chain of actions:



  1. first we convert the hexadecimal number to an int with .apply(int, base=16);

  2. next we convert this to binary data, with .apply(bin);

  3. next we chunk off the first two characters with .str[2:];

  4. then we obtain the last three characters with .str[-3:]; and

  5. finally we again interpret these as ints, with .apply(int, base=2).

So:



>>> df.Data.apply(int, base=16).apply(bin).str[2:].str[-3:].apply(int, base=2)
0 2
1 3
2 3
3 7
4 7
5 0
6 3
Name: Data, dtype: int64


We can however use another strategy here:



  1. we first convert the hexadecimal number to an int; and

  2. then we apply a bitwise and with 0b111.

for example:



>>> df.Data.apply(int, base=16) & 0b111
0 2
1 3
2 3
3 7
4 7
5 0
6 3
Name: Data, dtype: int64


The second attempt is not only simpler, but faster as well, approximately by 66%:



>>> timeit(first_strategy, number=10000)
6.962630775000434
>>> timeit(second_strategy, number=10000)
2.330652763019316


for a dataframe that repeats the sample data 100 times, we get:



>>> timeit(first_strategy, number=10000)
17.603060900000855
>>> timeit(second_strategy, number=10000)
5.901462858979357


this is again 66% faster.






share|improve this answer




















  • 1





    I like the other strategy... I might be tempted to use 0b111 instead of 7 (or possibly (1 << N) - 1 if it's going to be "the last N bits" where N is not just a couple ) or something but...

    – Jon Clements
    Nov 11 '18 at 21:18












  • @JonClements: thanks for the suggestion, edited.

    – Willem Van Onsem
    Nov 11 '18 at 21:26











  • Thank you very much. It works...but if I have to extract 3 bits from the 2nd to 5th position in a byte (for example, from "10010110" it is "010"), what I have to do? For the first solution, I could put str[p1:p2] and use None if it is the end of a string. But for the second solution, which by the way I like very much, how to extract bits that I want?

    – slobokv83
    Nov 12 '18 at 7:50











  • @slobokv83: you can first divide it by (1<<2) (so 4), like (df.Data.apply(int, base=16) // (1 << 2)) & 0b111

    – Willem Van Onsem
    Nov 12 '18 at 11:10






  • 1





    @slobokv83: well as said, you can use (df.Data.apply(int, base=16) // (1 << o)) & ((1 << w) - 1) to obtain the values between the bits o and o+w, no need to slice, zfill`, etc.

    – Willem Van Onsem
    Nov 12 '18 at 12:05













3












3








3







We can do this by a chain of actions:



  1. first we convert the hexadecimal number to an int with .apply(int, base=16);

  2. next we convert this to binary data, with .apply(bin);

  3. next we chunk off the first two characters with .str[2:];

  4. then we obtain the last three characters with .str[-3:]; and

  5. finally we again interpret these as ints, with .apply(int, base=2).

So:



>>> df.Data.apply(int, base=16).apply(bin).str[2:].str[-3:].apply(int, base=2)
0 2
1 3
2 3
3 7
4 7
5 0
6 3
Name: Data, dtype: int64


We can however use another strategy here:



  1. we first convert the hexadecimal number to an int; and

  2. then we apply a bitwise and with 0b111.

for example:



>>> df.Data.apply(int, base=16) & 0b111
0 2
1 3
2 3
3 7
4 7
5 0
6 3
Name: Data, dtype: int64


The second attempt is not only simpler, but faster as well, approximately by 66%:



>>> timeit(first_strategy, number=10000)
6.962630775000434
>>> timeit(second_strategy, number=10000)
2.330652763019316


for a dataframe that repeats the sample data 100 times, we get:



>>> timeit(first_strategy, number=10000)
17.603060900000855
>>> timeit(second_strategy, number=10000)
5.901462858979357


this is again 66% faster.






share|improve this answer















We can do this by a chain of actions:



  1. first we convert the hexadecimal number to an int with .apply(int, base=16);

  2. next we convert this to binary data, with .apply(bin);

  3. next we chunk off the first two characters with .str[2:];

  4. then we obtain the last three characters with .str[-3:]; and

  5. finally we again interpret these as ints, with .apply(int, base=2).

So:



>>> df.Data.apply(int, base=16).apply(bin).str[2:].str[-3:].apply(int, base=2)
0 2
1 3
2 3
3 7
4 7
5 0
6 3
Name: Data, dtype: int64


We can however use another strategy here:



  1. we first convert the hexadecimal number to an int; and

  2. then we apply a bitwise and with 0b111.

for example:



>>> df.Data.apply(int, base=16) & 0b111
0 2
1 3
2 3
3 7
4 7
5 0
6 3
Name: Data, dtype: int64


The second attempt is not only simpler, but faster as well, approximately by 66%:



>>> timeit(first_strategy, number=10000)
6.962630775000434
>>> timeit(second_strategy, number=10000)
2.330652763019316


for a dataframe that repeats the sample data 100 times, we get:



>>> timeit(first_strategy, number=10000)
17.603060900000855
>>> timeit(second_strategy, number=10000)
5.901462858979357


this is again 66% faster.







share|improve this answer














share|improve this answer



share|improve this answer








edited Nov 11 '18 at 21:35

























answered Nov 11 '18 at 21:16









Willem Van OnsemWillem Van Onsem

148k16142232




148k16142232







  • 1





    I like the other strategy... I might be tempted to use 0b111 instead of 7 (or possibly (1 << N) - 1 if it's going to be "the last N bits" where N is not just a couple ) or something but...

    – Jon Clements
    Nov 11 '18 at 21:18












  • @JonClements: thanks for the suggestion, edited.

    – Willem Van Onsem
    Nov 11 '18 at 21:26











  • Thank you very much. It works...but if I have to extract 3 bits from the 2nd to 5th position in a byte (for example, from "10010110" it is "010"), what I have to do? For the first solution, I could put str[p1:p2] and use None if it is the end of a string. But for the second solution, which by the way I like very much, how to extract bits that I want?

    – slobokv83
    Nov 12 '18 at 7:50











  • @slobokv83: you can first divide it by (1<<2) (so 4), like (df.Data.apply(int, base=16) // (1 << 2)) & 0b111

    – Willem Van Onsem
    Nov 12 '18 at 11:10






  • 1





    @slobokv83: well as said, you can use (df.Data.apply(int, base=16) // (1 << o)) & ((1 << w) - 1) to obtain the values between the bits o and o+w, no need to slice, zfill`, etc.

    – Willem Van Onsem
    Nov 12 '18 at 12:05












  • 1





    I like the other strategy... I might be tempted to use 0b111 instead of 7 (or possibly (1 << N) - 1 if it's going to be "the last N bits" where N is not just a couple ) or something but...

    – Jon Clements
    Nov 11 '18 at 21:18












  • @JonClements: thanks for the suggestion, edited.

    – Willem Van Onsem
    Nov 11 '18 at 21:26











  • Thank you very much. It works...but if I have to extract 3 bits from the 2nd to 5th position in a byte (for example, from "10010110" it is "010"), what I have to do? For the first solution, I could put str[p1:p2] and use None if it is the end of a string. But for the second solution, which by the way I like very much, how to extract bits that I want?

    – slobokv83
    Nov 12 '18 at 7:50











  • @slobokv83: you can first divide it by (1<<2) (so 4), like (df.Data.apply(int, base=16) // (1 << 2)) & 0b111

    – Willem Van Onsem
    Nov 12 '18 at 11:10






  • 1





    @slobokv83: well as said, you can use (df.Data.apply(int, base=16) // (1 << o)) & ((1 << w) - 1) to obtain the values between the bits o and o+w, no need to slice, zfill`, etc.

    – Willem Van Onsem
    Nov 12 '18 at 12:05







1




1





I like the other strategy... I might be tempted to use 0b111 instead of 7 (or possibly (1 << N) - 1 if it's going to be "the last N bits" where N is not just a couple ) or something but...

– Jon Clements
Nov 11 '18 at 21:18






I like the other strategy... I might be tempted to use 0b111 instead of 7 (or possibly (1 << N) - 1 if it's going to be "the last N bits" where N is not just a couple ) or something but...

– Jon Clements
Nov 11 '18 at 21:18














@JonClements: thanks for the suggestion, edited.

– Willem Van Onsem
Nov 11 '18 at 21:26





@JonClements: thanks for the suggestion, edited.

– Willem Van Onsem
Nov 11 '18 at 21:26













Thank you very much. It works...but if I have to extract 3 bits from the 2nd to 5th position in a byte (for example, from "10010110" it is "010"), what I have to do? For the first solution, I could put str[p1:p2] and use None if it is the end of a string. But for the second solution, which by the way I like very much, how to extract bits that I want?

– slobokv83
Nov 12 '18 at 7:50





Thank you very much. It works...but if I have to extract 3 bits from the 2nd to 5th position in a byte (for example, from "10010110" it is "010"), what I have to do? For the first solution, I could put str[p1:p2] and use None if it is the end of a string. But for the second solution, which by the way I like very much, how to extract bits that I want?

– slobokv83
Nov 12 '18 at 7:50













@slobokv83: you can first divide it by (1<<2) (so 4), like (df.Data.apply(int, base=16) // (1 << 2)) & 0b111

– Willem Van Onsem
Nov 12 '18 at 11:10





@slobokv83: you can first divide it by (1<<2) (so 4), like (df.Data.apply(int, base=16) // (1 << 2)) & 0b111

– Willem Van Onsem
Nov 12 '18 at 11:10




1




1





@slobokv83: well as said, you can use (df.Data.apply(int, base=16) // (1 << o)) & ((1 << w) - 1) to obtain the values between the bits o and o+w, no need to slice, zfill`, etc.

– Willem Van Onsem
Nov 12 '18 at 12:05





@slobokv83: well as said, you can use (df.Data.apply(int, base=16) // (1 << o)) & ((1 << w) - 1) to obtain the values between the bits o and o+w, no need to slice, zfill`, etc.

– Willem Van Onsem
Nov 12 '18 at 12:05













2














You can use:



df.Data.apply(lambda v: int(format(int(v, 16), '08b')[-3:], 2))


Which gives you:



0 2
1 3
2 3
3 7
4 7
5 0
6 3
Name: Data, dtype: int64


Those steps are:



  • Take your original data and convert it to decimal using int(number, 16) (base 16 is hex) (int('1A', 16) == 26)

  • Take that number and format it as a binary string format(number, '08b') gives you an character string of 0/1's zero filled on the left (format(26, '08b') == '00011010')

  • Take the last 3 characters of that string [-3:] ('010') and convert it to decimal with a base 2, int(binary_string[-3:], 2) gives you: 2





share|improve this answer























  • Thank you very much. It works fine...I have another question - if I need for the length of the bits array to be variable, what I have to do? You put '08b', and if I want in some moment to be '16b', should I put like 'lengthb' and for length give some value?

    – slobokv83
    Nov 12 '18 at 7:58















2














You can use:



df.Data.apply(lambda v: int(format(int(v, 16), '08b')[-3:], 2))


Which gives you:



0 2
1 3
2 3
3 7
4 7
5 0
6 3
Name: Data, dtype: int64


Those steps are:



  • Take your original data and convert it to decimal using int(number, 16) (base 16 is hex) (int('1A', 16) == 26)

  • Take that number and format it as a binary string format(number, '08b') gives you an character string of 0/1's zero filled on the left (format(26, '08b') == '00011010')

  • Take the last 3 characters of that string [-3:] ('010') and convert it to decimal with a base 2, int(binary_string[-3:], 2) gives you: 2





share|improve this answer























  • Thank you very much. It works fine...I have another question - if I need for the length of the bits array to be variable, what I have to do? You put '08b', and if I want in some moment to be '16b', should I put like 'lengthb' and for length give some value?

    – slobokv83
    Nov 12 '18 at 7:58













2












2








2







You can use:



df.Data.apply(lambda v: int(format(int(v, 16), '08b')[-3:], 2))


Which gives you:



0 2
1 3
2 3
3 7
4 7
5 0
6 3
Name: Data, dtype: int64


Those steps are:



  • Take your original data and convert it to decimal using int(number, 16) (base 16 is hex) (int('1A', 16) == 26)

  • Take that number and format it as a binary string format(number, '08b') gives you an character string of 0/1's zero filled on the left (format(26, '08b') == '00011010')

  • Take the last 3 characters of that string [-3:] ('010') and convert it to decimal with a base 2, int(binary_string[-3:], 2) gives you: 2





share|improve this answer













You can use:



df.Data.apply(lambda v: int(format(int(v, 16), '08b')[-3:], 2))


Which gives you:



0 2
1 3
2 3
3 7
4 7
5 0
6 3
Name: Data, dtype: int64


Those steps are:



  • Take your original data and convert it to decimal using int(number, 16) (base 16 is hex) (int('1A', 16) == 26)

  • Take that number and format it as a binary string format(number, '08b') gives you an character string of 0/1's zero filled on the left (format(26, '08b') == '00011010')

  • Take the last 3 characters of that string [-3:] ('010') and convert it to decimal with a base 2, int(binary_string[-3:], 2) gives you: 2






share|improve this answer












share|improve this answer



share|improve this answer










answered Nov 11 '18 at 21:12









Jon ClementsJon Clements

99.3k19174219




99.3k19174219












  • Thank you very much. It works fine...I have another question - if I need for the length of the bits array to be variable, what I have to do? You put '08b', and if I want in some moment to be '16b', should I put like 'lengthb' and for length give some value?

    – slobokv83
    Nov 12 '18 at 7:58

















  • Thank you very much. It works fine...I have another question - if I need for the length of the bits array to be variable, what I have to do? You put '08b', and if I want in some moment to be '16b', should I put like 'lengthb' and for length give some value?

    – slobokv83
    Nov 12 '18 at 7:58
















Thank you very much. It works fine...I have another question - if I need for the length of the bits array to be variable, what I have to do? You put '08b', and if I want in some moment to be '16b', should I put like 'lengthb' and for length give some value?

– slobokv83
Nov 12 '18 at 7:58





Thank you very much. It works fine...I have another question - if I need for the length of the bits array to be variable, what I have to do? You put '08b', and if I want in some moment to be '16b', should I put like 'lengthb' and for length give some value?

– slobokv83
Nov 12 '18 at 7:58

















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