Parsing column values in python pandas

Question

I have about 200.000 rows in df and 20 columns, and one column contains a name of the station. It looks like this:

00001 OPPT YY G
00002 LIMO DA G
000016 KAPAL VS G
0000663 TAPS VS G
...

What is the best way to take just numbers from column values? Desired output:

Thanks

user2285236 · Accepted Answer · 2017-06-17 11:44:19Z

1

Assuming Col1 is your column

df
Out: 
                Col1
0    00001 OPPT YY G
1    00002 LIMO DA G
2  000016 KAPAL VS G
3  0000663 TAPS VS G

Split on space and take the first element:

df['Col1'].str.split().str[0]
Out: 
0      00001
1      00002
2     000016
3    0000663
Name: Col1, dtype: object

answered Jun 17, 2017 at 11:44

user2285236

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2 Comments

jovicbg Over a year ago

Well, sometimes it can be different order, first word, then digit, my bad.

user2285236 Over a year ago

@jovicbg I think that requires regex and I am not very good at it. Can you un-accept the answer so people won't consider this solved and look at the question. It might be better to edit the question to include that by the way.

Alanuccio · Accepted Answer · 2019-10-30 05:28:46Z

1

May be smth like this:

df['col_1'] = df['col_1'].replace(r'^(\b\d+\b).*$', r'\1', regex=True)

edited Oct 30, 2019 at 5:28

answered Oct 30, 2019 at 5:13

Alanuccio

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Comments

bikuser · Accepted Answer · 2017-06-17 11:45:54Z

0

so you can use this function: for eg if your dataframe is df and your first column contain this data then:

(df.T).ix[0]

i hope this will help you.

edited Jun 17, 2017 at 11:45

answered Jun 17, 2017 at 11:39

bikuser

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