Mixing
Pandas exporting to_csv() with quotation marks around column names
For some reason I need to output to a csv in this format with quotations around each columns names, my desired output looks like:
"date" "ret"
2018-09-24 0.00013123989025119056
I am trying with
import csv
import pandas as pd
Y_pred.index.name = ""date""
Y_pred.name = "'ret'"
Y_pred = Y_pred.to_frame()
path = "prediction/Q1/"
try:
os.makedirs(path)
except:
pass
Y_pred.to_csv(path+instrument_tmp+"_ret.txt",sep=' ')
and got outputs like:
"""date""" 'ret'
2018-09-24 0.00013123989025119056
I can't seem to find a way to use quotation to wrap at the columns. Does anyone know how to? Thanks.
My solution:
using quoting=csv.QUOTE_NONE together with Y_pred.index.name = ""date"", Y_pred.name = ""ret""
Y_pred.index.name = ""date""
Y_pred.name = ""ret""
Y_pred = Y_pred.to_frame()
path = "prediction/Q1/"
try:
os.makedirs(path)
except:
pass
Y_pred.to_csv(path+instrument_tmp+"_ret.txt",sep=' ',quoting=csv.QUOTE_NONE)
and then I get
"date" "ret"
2018-09-24 0.00013123989025119056
pandas csv escaping export-to-csv quoting
edited Nov 20 '18 at 1:04
smci
14.7k672104
asked Nov 19 '18 at 23:25
user40780user40780
423826
add a comment |
For some reason I need to output to a csv in this format with quotations around each columns names, my desired output looks like:
"date" "ret"
2018-09-24 0.00013123989025119056
I am trying with
import csv
import pandas as pd
Y_pred.index.name = ""date""
Y_pred.name = "'ret'"
Y_pred = Y_pred.to_frame()
path = "prediction/Q1/"
try:
os.makedirs(path)
except:
pass
Y_pred.to_csv(path+instrument_tmp+"_ret.txt",sep=' ')
and got outputs like:
"""date""" 'ret'
2018-09-24 0.00013123989025119056
I can't seem to find a way to use quotation to wrap at the columns. Does anyone know how to? Thanks.
My solution:
using quoting=csv.QUOTE_NONE together with Y_pred.index.name = ""date"", Y_pred.name = ""ret""
Y_pred.index.name = ""date""
Y_pred.name = ""ret""
Y_pred = Y_pred.to_frame()
path = "prediction/Q1/"
try:
os.makedirs(path)
except:
pass
Y_pred.to_csv(path+instrument_tmp+"_ret.txt",sep=' ',quoting=csv.QUOTE_NONE)
and then I get
"date" "ret"
2018-09-24 0.00013123989025119056
pandas csv escaping export-to-csv quoting
edited Nov 20 '18 at 1:04
smci
14.7k672104
asked Nov 19 '18 at 23:25
user40780user40780
423826
This is called quoted output. In general there is no need to manually hack quotes into the column names. Use one of thequoting=csv.QUOTE_...options
– smci
Nov 20 '18 at 1:00
Possible duplicate of Quote only the required columns using pandas to_csv
– smci
Nov 20 '18 at 1:14
add a comment |
For some reason I need to output to a csv in this format with quotations around each columns names, my desired output looks like:
"date" "ret"
2018-09-24 0.00013123989025119056
I am trying with
import csv
import pandas as pd
Y_pred.index.name = ""date""
Y_pred.name = "'ret'"
Y_pred = Y_pred.to_frame()
path = "prediction/Q1/"
try:
os.makedirs(path)
except:
pass
Y_pred.to_csv(path+instrument_tmp+"_ret.txt",sep=' ')
and got outputs like:
"""date""" 'ret'
2018-09-24 0.00013123989025119056
I can't seem to find a way to use quotation to wrap at the columns. Does anyone know how to? Thanks.
My solution:
using quoting=csv.QUOTE_NONE together with Y_pred.index.name = ""date"", Y_pred.name = ""ret""
Y_pred.index.name = ""date""
Y_pred.name = ""ret""
Y_pred = Y_pred.to_frame()
path = "prediction/Q1/"
try:
os.makedirs(path)
except:
pass
Y_pred.to_csv(path+instrument_tmp+"_ret.txt",sep=' ',quoting=csv.QUOTE_NONE)
and then I get
"date" "ret"
2018-09-24 0.00013123989025119056
pandas csv escaping export-to-csv quoting
edited Nov 20 '18 at 1:04
smci
14.7k672104
asked Nov 19 '18 at 23:25
user40780user40780
423826
For some reason I need to output to a csv in this format with quotations around each columns names, my desired output looks like:
"date" "ret"
2018-09-24 0.00013123989025119056
I am trying with
import csv
import pandas as pd
Y_pred.index.name = ""date""
Y_pred.name = "'ret'"
Y_pred = Y_pred.to_frame()
path = "prediction/Q1/"
try:
os.makedirs(path)
except:
pass
Y_pred.to_csv(path+instrument_tmp+"_ret.txt",sep=' ')
and got outputs like:
"""date""" 'ret'
2018-09-24 0.00013123989025119056
I can't seem to find a way to use quotation to wrap at the columns. Does anyone know how to? Thanks.
My solution:
using quoting=csv.QUOTE_NONE together with Y_pred.index.name = ""date"", Y_pred.name = ""ret""
Y_pred.index.name = ""date""
Y_pred.name = ""ret""
Y_pred = Y_pred.to_frame()
path = "prediction/Q1/"
try:
os.makedirs(path)
except:
pass
Y_pred.to_csv(path+instrument_tmp+"_ret.txt",sep=' ',quoting=csv.QUOTE_NONE)
and then I get
"date" "ret"
2018-09-24 0.00013123989025119056
pandas csv escaping export-to-csv quoting
pandas csv escaping export-to-csv quoting
edited Nov 20 '18 at 1:04
smci
14.7k672104
asked Nov 19 '18 at 23:25
user40780user40780
423826
edited Nov 20 '18 at 1:04
smci
14.7k672104
asked Nov 19 '18 at 23:25
user40780user40780
423826
edited Nov 20 '18 at 1:04
smci
14.7k672104
edited Nov 20 '18 at 1:04
smci
14.7k672104
edited Nov 20 '18 at 1:04
smci
14.7k672104
14.7k672104
asked Nov 19 '18 at 23:25
user40780user40780
423826
asked Nov 19 '18 at 23:25
user40780user40780
423826
asked Nov 19 '18 at 23:25
user40780user40780
423826
423826
This is called quoted output. In general there is no need to manually hack quotes into the column names. Use one of thequoting=csv.QUOTE_...options
– smci
Nov 20 '18 at 1:00
Possible duplicate of Quote only the required columns using pandas to_csv
– smci
Nov 20 '18 at 1:14
add a comment |
This is called quoted output. In general there is no need to manually hack quotes into the column names. Use one of thequoting=csv.QUOTE_...options
– smci
Nov 20 '18 at 1:00
Possible duplicate of Quote only the required columns using pandas to_csv
– smci
Nov 20 '18 at 1:14
This is called quoted output. In general there is no need to manually hack quotes into the column names. Use one of the
quoting=csv.QUOTE_... options– smci
Nov 20 '18 at 1:00
This is called quoted output. In general there is no need to manually hack quotes into the column names. Use one of the
quoting=csv.QUOTE_... options– smci
Nov 20 '18 at 1:00
Possible duplicate of Quote only the required columns using pandas to_csv
– smci
Nov 20 '18 at 1:14
Possible duplicate of Quote only the required columns using pandas to_csv
– smci
Nov 20 '18 at 1:14
add a comment |
2 Answers
2
active
oldest
votes
IIUC, you can use the quoting argument with csv.QUOTE_NONE
import csv
df.to_csv('test.csv',sep=' ',quoting=csv.QUOTE_NONE)
And your resulting csv will look like:
"date" "ret"
0 2018-09-24 0.00013123989025119056
Side Note: To facilitate the adding of quotations to your columns, you can use add_prefix and add_suffix. If your starting dataframe looks like:
>>> df
date ret
0 2018-09-24 0.000131
Then do:
df = df.add_suffix('"').add_prefix('"')
df.to_csv('test.csv',sep=' ',quoting=csv.QUOTE_NONE)
answered Nov 19 '18 at 23:34
saculsacul
30k41740
is this version dependent? I didn't get the desired output when quoting=csv.QUOTE_NONE
– user40780
Nov 19 '18 at 23:41
I wouldn't think so, but just for reference I'm using '0.21.1'
– sacul
Nov 19 '18 at 23:42
add a comment |
This is called quoted output.
Instead of manually hacking in quotes into your column names (which will mess with other dataframe functionality), use the quoting option:
df = pd.DataFrame({"date": ["2018-09-24"], "ret": [0.00013123989025119056]})
df.to_csv("out_q_esc.txt", sep=' ', escapechar='\', quoting=csv.QUOTE_ALL, index=None)
"date" "ret"
"2018-09-24" "0.00013123989025119056"
The 'correct' way is to use quoting=csv.QUOTE_ALL (and optionally escapechar='\'), but note however that QUOTE_ALL will force all columns to be quoted, even obviously numeric ones like the index; if we hadn't specified index=None, we would get:
"" "date" "ret"
"0" "2018-09-24" "0.00013123989025119056"
csv.QUOTE_MINIMALrefuses to quote these fields because they don't strictly need quotes (they're neither multiline nor do they contain internal quote or separator chars)
answered Nov 20 '18 at 0:58
smcismci
14.7k672104
add a comment |
Your Answer
StackExchange.ifUsing("editor", function () {
StackExchange.using("externalEditor", function () {
StackExchange.using("snippets", function () {
StackExchange.snippets.init();
});
});
}, "code-snippets");
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "1"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});
function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: true,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: 10,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});
}
});
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53384099%2fpandas-exporting-to-csv-with-quotation-marks-around-column-names%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
IIUC, you can use the quoting argument with csv.QUOTE_NONE
import csv
df.to_csv('test.csv',sep=' ',quoting=csv.QUOTE_NONE)
And your resulting csv will look like:
"date" "ret"
0 2018-09-24 0.00013123989025119056
Side Note: To facilitate the adding of quotations to your columns, you can use add_prefix and add_suffix. If your starting dataframe looks like:
>>> df
date ret
0 2018-09-24 0.000131
Then do:
df = df.add_suffix('"').add_prefix('"')
df.to_csv('test.csv',sep=' ',quoting=csv.QUOTE_NONE)
answered Nov 19 '18 at 23:34
saculsacul
30k41740
is this version dependent? I didn't get the desired output when quoting=csv.QUOTE_NONE
– user40780
Nov 19 '18 at 23:41
I wouldn't think so, but just for reference I'm using '0.21.1'
– sacul
Nov 19 '18 at 23:42
add a comment |
IIUC, you can use the quoting argument with csv.QUOTE_NONE
import csv
df.to_csv('test.csv',sep=' ',quoting=csv.QUOTE_NONE)
And your resulting csv will look like:
"date" "ret"
0 2018-09-24 0.00013123989025119056
Side Note: To facilitate the adding of quotations to your columns, you can use add_prefix and add_suffix. If your starting dataframe looks like:
>>> df
date ret
0 2018-09-24 0.000131
Then do:
df = df.add_suffix('"').add_prefix('"')
df.to_csv('test.csv',sep=' ',quoting=csv.QUOTE_NONE)
answered Nov 19 '18 at 23:34
saculsacul
30k41740
is this version dependent? I didn't get the desired output when quoting=csv.QUOTE_NONE
– user40780
Nov 19 '18 at 23:41
I wouldn't think so, but just for reference I'm using '0.21.1'
– sacul
Nov 19 '18 at 23:42
add a comment |
IIUC, you can use the quoting argument with csv.QUOTE_NONE
import csv
df.to_csv('test.csv',sep=' ',quoting=csv.QUOTE_NONE)
And your resulting csv will look like:
"date" "ret"
0 2018-09-24 0.00013123989025119056
Side Note: To facilitate the adding of quotations to your columns, you can use add_prefix and add_suffix. If your starting dataframe looks like:
>>> df
date ret
0 2018-09-24 0.000131
Then do:
df = df.add_suffix('"').add_prefix('"')
df.to_csv('test.csv',sep=' ',quoting=csv.QUOTE_NONE)
answered Nov 19 '18 at 23:34
saculsacul
30k41740
IIUC, you can use the quoting argument with csv.QUOTE_NONE
import csv
df.to_csv('test.csv',sep=' ',quoting=csv.QUOTE_NONE)
And your resulting csv will look like:
"date" "ret"
0 2018-09-24 0.00013123989025119056
Side Note: To facilitate the adding of quotations to your columns, you can use add_prefix and add_suffix. If your starting dataframe looks like:
>>> df
date ret
0 2018-09-24 0.000131
Then do:
df = df.add_suffix('"').add_prefix('"')
df.to_csv('test.csv',sep=' ',quoting=csv.QUOTE_NONE)
answered Nov 19 '18 at 23:34
saculsacul
30k41740
answered Nov 19 '18 at 23:34
saculsacul
30k41740
answered Nov 19 '18 at 23:34
saculsacul
30k41740
answered Nov 19 '18 at 23:34
saculsacul
30k41740
30k41740
is this version dependent? I didn't get the desired output when quoting=csv.QUOTE_NONE
– user40780
Nov 19 '18 at 23:41
I wouldn't think so, but just for reference I'm using '0.21.1'
– sacul
Nov 19 '18 at 23:42
add a comment |
is this version dependent? I didn't get the desired output when quoting=csv.QUOTE_NONE
– user40780
Nov 19 '18 at 23:41
I wouldn't think so, but just for reference I'm using '0.21.1'
– sacul
Nov 19 '18 at 23:42
is this version dependent? I didn't get the desired output when quoting=csv.QUOTE_NONE
– user40780
Nov 19 '18 at 23:41
is this version dependent? I didn't get the desired output when quoting=csv.QUOTE_NONE
– user40780
Nov 19 '18 at 23:41
I wouldn't think so, but just for reference I'm using '0.21.1'
– sacul
Nov 19 '18 at 23:42
I wouldn't think so, but just for reference I'm using '0.21.1'
– sacul
Nov 19 '18 at 23:42
add a comment |
This is called quoted output.
Instead of manually hacking in quotes into your column names (which will mess with other dataframe functionality), use the quoting option:
df = pd.DataFrame({"date": ["2018-09-24"], "ret": [0.00013123989025119056]})
df.to_csv("out_q_esc.txt", sep=' ', escapechar='\', quoting=csv.QUOTE_ALL, index=None)
"date" "ret"
"2018-09-24" "0.00013123989025119056"
The 'correct' way is to use quoting=csv.QUOTE_ALL (and optionally escapechar='\'), but note however that QUOTE_ALL will force all columns to be quoted, even obviously numeric ones like the index; if we hadn't specified index=None, we would get:
"" "date" "ret"
"0" "2018-09-24" "0.00013123989025119056"
csv.QUOTE_MINIMALrefuses to quote these fields because they don't strictly need quotes (they're neither multiline nor do they contain internal quote or separator chars)
answered Nov 20 '18 at 0:58
smcismci
14.7k672104
add a comment |
This is called quoted output.
Instead of manually hacking in quotes into your column names (which will mess with other dataframe functionality), use the quoting option:
df = pd.DataFrame({"date": ["2018-09-24"], "ret": [0.00013123989025119056]})
df.to_csv("out_q_esc.txt", sep=' ', escapechar='\', quoting=csv.QUOTE_ALL, index=None)
"date" "ret"
"2018-09-24" "0.00013123989025119056"
The 'correct' way is to use quoting=csv.QUOTE_ALL (and optionally escapechar='\'), but note however that QUOTE_ALL will force all columns to be quoted, even obviously numeric ones like the index; if we hadn't specified index=None, we would get:
"" "date" "ret"
"0" "2018-09-24" "0.00013123989025119056"
csv.QUOTE_MINIMALrefuses to quote these fields because they don't strictly need quotes (they're neither multiline nor do they contain internal quote or separator chars)
answered Nov 20 '18 at 0:58
smcismci
14.7k672104
add a comment |
This is called quoted output.
Instead of manually hacking in quotes into your column names (which will mess with other dataframe functionality), use the quoting option:
df = pd.DataFrame({"date": ["2018-09-24"], "ret": [0.00013123989025119056]})
df.to_csv("out_q_esc.txt", sep=' ', escapechar='\', quoting=csv.QUOTE_ALL, index=None)
"date" "ret"
"2018-09-24" "0.00013123989025119056"
The 'correct' way is to use quoting=csv.QUOTE_ALL (and optionally escapechar='\'), but note however that QUOTE_ALL will force all columns to be quoted, even obviously numeric ones like the index; if we hadn't specified index=None, we would get:
"" "date" "ret"
"0" "2018-09-24" "0.00013123989025119056"
csv.QUOTE_MINIMALrefuses to quote these fields because they don't strictly need quotes (they're neither multiline nor do they contain internal quote or separator chars)
answered Nov 20 '18 at 0:58
smcismci
14.7k672104
This is called quoted output.
Instead of manually hacking in quotes into your column names (which will mess with other dataframe functionality), use the quoting option:
df = pd.DataFrame({"date": ["2018-09-24"], "ret": [0.00013123989025119056]})
df.to_csv("out_q_esc.txt", sep=' ', escapechar='\', quoting=csv.QUOTE_ALL, index=None)
"date" "ret"
"2018-09-24" "0.00013123989025119056"
The 'correct' way is to use quoting=csv.QUOTE_ALL (and optionally escapechar='\'), but note however that QUOTE_ALL will force all columns to be quoted, even obviously numeric ones like the index; if we hadn't specified index=None, we would get:
"" "date" "ret"
"0" "2018-09-24" "0.00013123989025119056"
csv.QUOTE_MINIMALrefuses to quote these fields because they don't strictly need quotes (they're neither multiline nor do they contain internal quote or separator chars)
answered Nov 20 '18 at 0:58
smcismci
14.7k672104
edited Nov 20 '18 at 1:09
answered Nov 20 '18 at 0:58
smcismci
14.7k672104
answered Nov 20 '18 at 0:58
smcismci
14.7k672104
answered Nov 20 '18 at 0:58
smcismci
14.7k672104
14.7k672104
add a comment |
add a comment |
Thanks for contributing an answer to Stack Overflow!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53384099%2fpandas-exporting-to-csv-with-quotation-marks-around-column-names%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
This is called quoted output. In general there is no need to manually hack quotes into the column names. Use one of the
quoting=csv.QUOTE_...options– smci
Nov 20 '18 at 1:00
Possible duplicate of Quote only the required columns using pandas to_csv
– smci
Nov 20 '18 at 1:14