Pandas - read csv stored as string in memory to data frame

Question

With comma separated text stored in a var like below

data = """
Class,Name,Long,Lat
A,ABC11,139.6295542,35.61144069
A,ABC20,139.630596,35.61045559
A,ABC03,139.6300307,35.61327781
B,ABC54,139.7787818,35.68847945
B,ABC05,139.7814447,35.6816882
B,ABC06,139.7788191,35.681865
B,ABC24,139.7790396,35.67781697
"""

is there a quick way to read this into a pandas data frame without have to store to a file and use pd.read_csv(). I'm coming from R and it provides a nice way to do this like below.

text <- "
State,District,County,Num Voters,Total Votes in State,Votes for None,Candidate Name,Party,Votes Scored
CA,San Diego,Delmar,190962,48026634,2511,A1,IND,949
CA,San Diego,Delmar,190962,48026634,2511,A2,RP(K),44815
"
df <- read.table(textConnection(text), sep = ",", header = TRUE)

stackoverflow.com/questions/22604564/… It's already answered here. — Danny
– Danny, Commented Oct 8, 2019 at 14:25

RomanPerekhrest · Accepted Answer · 2019-10-08 14:21:17Z

28

With io.StringIO object (in-memory stream for text I/O):

import pandas as pd
from io import StringIO

data = """
Class,Name,Long,Lat
A,ABC11,139.6295542,35.61144069
A,ABC20,139.630596,35.61045559
A,ABC03,139.6300307,35.61327781
B,ABC54,139.7787818,35.68847945
B,ABC05,139.7814447,35.6816882
B,ABC06,139.7788191,35.681865
B,ABC24,139.7790396,35.67781697
"""

df = pd.read_csv(StringIO(data))
print(df)

The output:

  Class   Name        Long        Lat
0     A  ABC11  139.629554  35.611441
1     A  ABC20  139.630596  35.610456
2     A  ABC03  139.630031  35.613278
3     B  ABC54  139.778782  35.688479
4     B  ABC05  139.781445  35.681688
5     B  ABC06  139.778819  35.681865
6     B  ABC24  139.779040  35.677817

answered Oct 8, 2019 at 14:21

RomanPerekhrest

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Comments

zigzag · Accepted Answer · 2019-10-08 14:56:10Z

-3

from prettytable import PrettyTable

def create_table(data):
    data = data.strip().split('\n')
    pt = PrettyTable()
    pt.field_names = data[0].split(',')

    for row in data[1:]:
        pt.add_row(row.split(','))

    return pt

data = """
Class,Name,Long,Lat
A,ABC11,139.6295542,35.61144069
A,ABC20,139.630596,35.61045559
A,ABC03,139.6300307,35.61327781
B,ABC54,139.7787818,35.68847945
B,ABC05,139.7814447,35.6816882
B,ABC06,139.7788191,35.681865
B,ABC24,139.7790396,35.67781697
"""

table = create_table(data)

print(table)
+-------+-------+-------------+-------------+
| Class |  Name |     Long    |     Lat     |
+-------+-------+-------------+-------------+
|   A   | ABC11 | 139.6295542 | 35.61144069 |
|   A   | ABC20 |  139.630596 | 35.61045559 |
|   A   | ABC03 | 139.6300307 | 35.61327781 |
|   B   | ABC54 | 139.7787818 | 35.68847945 |
|   B   | ABC05 | 139.7814447 |  35.6816882 |
|   B   | ABC06 | 139.7788191 |  35.681865  |
|   B   | ABC24 | 139.7790396 | 35.67781697 |
+-------+-------+-------------+-------------+

or

from prettytable import from_csv
from io import StringIO

table = from_csv(StringIO(data))

print(table)

answered Oct 8, 2019 at 14:56

zigzag

1488 bronze badges

1 Comment

bluenote10 Over a year ago

That doesn't return an instance of pandas.DataFrame as the question asks for, but an instance of prettytable.PrettyTable.

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