python pandas csv_read put all row in first cell of the row

Question

I am playing with famous titanic data. I have data csv with comma separation. And data looks like this:

passengerId,survived,pclass,name,sex,age,sibSp,parch,ticket,fare,cabin,embarked
1,0,3,"Braund, Mr. Owen Harris",male,22,1,0,A/5 21171,7.25,,S
2,1,1,"Cumings, Mrs. John Bradley (Florence Briggs Thayer)",female,38,1,0,PC 17599,71.2833,C85,C

I am trying to use pandas.csv_read but it doesn't work.

My code:

import pandas as pd

titanic = pd.read_csv('titanic.csv')
print(titanic.head(10))

I tried couple combinations with argues of the csv_read method: sep = ',', decimal = ',', delimiter = ',' and still I got the same output which is:

                                         passengerId  survived  ...  cabin  embarked
0  1,0,3,"Braund, Mr. Owen Harris",male,22,1,0,A/...       NaN  ...    NaN       NaN
1  2,1,1,"Cumings, Mrs. John Bradley (Florence Br...       NaN  ...    NaN       NaN
2  3,1,3,"Heikkinen, Miss. Laina",female,26,0,0,S...       NaN  ...    NaN       NaN

I tryied to search in other stackoverflow questions but I couldn't find an answer. Thank you for your help.

How working `pd.read_csv('titanic.csv', quoting=3)` ? What is your pandas version? — jezrael, Dec 19 '19 at 12:32
But now I can see that I have a transposition in data. Survived column has values of pclass values and so on. ;( — Karollo, Dec 19 '19 at 12:38
It seems some data problem, `quoting=3` is used for ignore all quotes. — jezrael, Dec 19 '19 at 12:40
Yes, but if you ignore all quotes in a row then in column name you have a quote so column name is spliting on two columns: name and sex — Karollo, Dec 19 '19 at 13:17

score 0 · Answer 1 · answered Dec 19 '19 at 12:55

It seems like the problem is that you have some commas inside your columns.

The quotechar parameter might help you since it will tell pandas to ignore commas between the char specified (")

titanic = pd.read_csv('titanic.csv', quotechar='"', sep=",")

python pandas csv_read put all row in first cell of the row

1 Answers1