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Cleaning the special characters and converting float into int for multiple columns in Python, Pandas
Convert hex string to int in PythonHow do I parse a string to a float or int?What is a clean, pythonic way to have multiple constructors in Python?Peak detection in a 2D arraySelecting multiple columns in a pandas dataframeAdding new column to existing DataFrame in Python pandas“Large data” work flows using pandasConvert floats to ints in Pandas?how to convert object data type into float in python data framePandas removing all special characters from columns
.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty margin-bottom:0;
I am cleaning a large dataset which has 300 columns. Most of the columns have special characters and float. How to remove the special characters and convert the float into int? I have close to 20 columns. Please suggest.
Sample columns
Column 1
5.179411048
6.979664266
6.801623755
6.357895491
5.672671138
5.986308293
6.916835392
6.113538245
7.854630746
6.264289168
6.183119587
5.838588332
6.840507371
8.333833257
6.188446205
8.309021165
7.34162041
5.230597972
5.247489061
8.181107798
5.536886048
6.313108318
8.128615238
Column 2
5.959064936999185H
5.559656080630483G
4.984461828692988B
5.160616481113521Z
6.2C$$@@@
5.462299069965385P
5.23564876@4126072G
5.275847049000189J
5.13407947424$9958G
5.204035084141148R
5.625365837737466W
5.551530319919428T
5.143210079430139Q
python python-3.x pandas python-2.7
edited Mar 28 at 9:04
martineau
75.5k11 gold badges103 silver badges198 bronze badges
asked Mar 28 at 6:51
JasonJason
367 bronze badges
add a comment |
I am cleaning a large dataset which has 300 columns. Most of the columns have special characters and float. How to remove the special characters and convert the float into int? I have close to 20 columns. Please suggest.
Sample columns
Column 1
5.179411048
6.979664266
6.801623755
6.357895491
5.672671138
5.986308293
6.916835392
6.113538245
7.854630746
6.264289168
6.183119587
5.838588332
6.840507371
8.333833257
6.188446205
8.309021165
7.34162041
5.230597972
5.247489061
8.181107798
5.536886048
6.313108318
8.128615238
Column 2
5.959064936999185H
5.559656080630483G
4.984461828692988B
5.160616481113521Z
6.2C$$@@@
5.462299069965385P
5.23564876@4126072G
5.275847049000189J
5.13407947424$9958G
5.204035084141148R
5.625365837737466W
5.551530319919428T
5.143210079430139Q
python python-3.x pandas python-2.7
edited Mar 28 at 9:04
martineau
75.5k11 gold badges103 silver badges198 bronze badges
asked Mar 28 at 6:51
JasonJason
367 bronze badges
300 colummns or 20 columns?
– Yunnosch
Mar 28 at 6:52
Useregexto get number out of it and convert it into int. you should provide expected output too.
– AkshayNevrekar
Mar 28 at 6:53
2
Please do not confuse StackOverflow for being a free code writing service. Take the tour, read How to Ask and maybe codeblog.jonskeet.uk/2012/11/24/… What did you try yourself?
– Yunnosch
Mar 28 at 6:53
@Yunnosch Datasets have 300 coulmns. I need to clean 20 columns which has characters and float
– Jason
Mar 28 at 6:56
add a comment |
I am cleaning a large dataset which has 300 columns. Most of the columns have special characters and float. How to remove the special characters and convert the float into int? I have close to 20 columns. Please suggest.
Sample columns
Column 1
5.179411048
6.979664266
6.801623755
6.357895491
5.672671138
5.986308293
6.916835392
6.113538245
7.854630746
6.264289168
6.183119587
5.838588332
6.840507371
8.333833257
6.188446205
8.309021165
7.34162041
5.230597972
5.247489061
8.181107798
5.536886048
6.313108318
8.128615238
Column 2
5.959064936999185H
5.559656080630483G
4.984461828692988B
5.160616481113521Z
6.2C$$@@@
5.462299069965385P
5.23564876@4126072G
5.275847049000189J
5.13407947424$9958G
5.204035084141148R
5.625365837737466W
5.551530319919428T
5.143210079430139Q
python python-3.x pandas python-2.7
edited Mar 28 at 9:04
martineau
75.5k11 gold badges103 silver badges198 bronze badges
asked Mar 28 at 6:51
JasonJason
367 bronze badges
I am cleaning a large dataset which has 300 columns. Most of the columns have special characters and float. How to remove the special characters and convert the float into int? I have close to 20 columns. Please suggest.
Sample columns
Column 1
5.179411048
6.979664266
6.801623755
6.357895491
5.672671138
5.986308293
6.916835392
6.113538245
7.854630746
6.264289168
6.183119587
5.838588332
6.840507371
8.333833257
6.188446205
8.309021165
7.34162041
5.230597972
5.247489061
8.181107798
5.536886048
6.313108318
8.128615238
Column 2
5.959064936999185H
5.559656080630483G
4.984461828692988B
5.160616481113521Z
6.2C$$@@@
5.462299069965385P
5.23564876@4126072G
5.275847049000189J
5.13407947424$9958G
5.204035084141148R
5.625365837737466W
5.551530319919428T
5.143210079430139Q
python python-3.x pandas python-2.7
python python-3.x pandas python-2.7
edited Mar 28 at 9:04
martineau
75.5k11 gold badges103 silver badges198 bronze badges
asked Mar 28 at 6:51
JasonJason
367 bronze badges
edited Mar 28 at 9:04
martineau
75.5k11 gold badges103 silver badges198 bronze badges
asked Mar 28 at 6:51
JasonJason
367 bronze badges
edited Mar 28 at 9:04
martineau
75.5k11 gold badges103 silver badges198 bronze badges
edited Mar 28 at 9:04
martineau
75.5k11 gold badges103 silver badges198 bronze badges
edited Mar 28 at 9:04
martineau
75.5k11 gold badges103 silver badges198 bronze badges
75.5k11 gold badges103 silver badges198 bronze badges
asked Mar 28 at 6:51
JasonJason
367 bronze badges
asked Mar 28 at 6:51
JasonJason
367 bronze badges
asked Mar 28 at 6:51
JasonJason
367 bronze badges
367 bronze badges
300 colummns or 20 columns?
– Yunnosch
Mar 28 at 6:52
Useregexto get number out of it and convert it into int. you should provide expected output too.
– AkshayNevrekar
Mar 28 at 6:53
2
Please do not confuse StackOverflow for being a free code writing service. Take the tour, read How to Ask and maybe codeblog.jonskeet.uk/2012/11/24/… What did you try yourself?
– Yunnosch
Mar 28 at 6:53
@Yunnosch Datasets have 300 coulmns. I need to clean 20 columns which has characters and float
– Jason
Mar 28 at 6:56
add a comment |
300 colummns or 20 columns?
– Yunnosch
Mar 28 at 6:52
Useregexto get number out of it and convert it into int. you should provide expected output too.
– AkshayNevrekar
Mar 28 at 6:53
2
Please do not confuse StackOverflow for being a free code writing service. Take the tour, read How to Ask and maybe codeblog.jonskeet.uk/2012/11/24/… What did you try yourself?
– Yunnosch
Mar 28 at 6:53
@Yunnosch Datasets have 300 coulmns. I need to clean 20 columns which has characters and float
– Jason
Mar 28 at 6:56
300 colummns or 20 columns?
– Yunnosch
Mar 28 at 6:52
300 colummns or 20 columns?
– Yunnosch
Mar 28 at 6:52
Use
regex to get number out of it and convert it into int. you should provide expected output too.– AkshayNevrekar
Mar 28 at 6:53
Use
regex to get number out of it and convert it into int. you should provide expected output too.– AkshayNevrekar
Mar 28 at 6:53
2
2
Please do not confuse StackOverflow for being a free code writing service. Take the tour, read How to Ask and maybe codeblog.jonskeet.uk/2012/11/24/… What did you try yourself?
– Yunnosch
Mar 28 at 6:53
Please do not confuse StackOverflow for being a free code writing service. Take the tour, read How to Ask and maybe codeblog.jonskeet.uk/2012/11/24/… What did you try yourself?
– Yunnosch
Mar 28 at 6:53
@Yunnosch Datasets have 300 coulmns. I need to clean 20 columns which has characters and float
– Jason
Mar 28 at 6:56
@Yunnosch Datasets have 300 coulmns. I need to clean 20 columns which has characters and float
– Jason
Mar 28 at 6:56
add a comment |
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300 colummns or 20 columns?
– Yunnosch
Mar 28 at 6:52
Use
regexto get number out of it and convert it into int. you should provide expected output too.– AkshayNevrekar
Mar 28 at 6:53
2
Please do not confuse StackOverflow for being a free code writing service. Take the tour, read How to Ask and maybe codeblog.jonskeet.uk/2012/11/24/… What did you try yourself?
– Yunnosch
Mar 28 at 6:53
@Yunnosch Datasets have 300 coulmns. I need to clean 20 columns which has characters and float
– Jason
Mar 28 at 6:56