I want to find the datatype of all the variables in a csv file in python. In R we can achieve the same using str()
command .
str(data_frame)
this gives an output like this
> str(train)
'data.frame': 891 obs. of 12 variables:
$ PassengerId: int 1 2 3 4 5 6 7 8 9 10 ...
$ Survived : int 0 1 1 1 0 0 0 0 1 1 ...
$ Pclass : int 3 1 3 1 3 3 1 3 3 2 ...
$ Name : Factor w/ 891 levels "Abbing, Mr. Anthony",..: 109 191 358 277 16 559 520 629 417 581 ...
$ Sex : Factor w/ 2 levels "female","male": 2 1 1 1 2 2 2 2 1 1 ...
$ Age : num 22 38 26 35 35 NA 54 2 27 14 ...
$ SibSp : int 1 1 0 1 0 0 0 3 0 1 ...
$ Parch : int 0 0 0 0 0 0 0 1 2 0 ...
$ Ticket : Factor w/ 681 levels "110152","110413",..: 524 597 670 50 473 276 86 396 345 133 ...
$ Fare : num 7.25 71.28 7.92 53.1 8.05 ...
$ Cabin : Factor w/ 148 levels "","A10","A14",..: 1 83 1 57 1 1 131 1 1 1 ...
$ Embarked : Factor w/ 4 levels "","C","Q","S": 4 2 4 4 4 3 4 4 4 2 ...
is there a similar way in python?
You probably want dtypes
>>> import pandas as pd
>>> df = pd.DataFrame({'foo': [1, 2, 3], 'bar': [1.0, 2.0, 3.0], 'baz': ['qux', 'quux', 'quuux']})
>>> df.dtypes
bar float64
baz object
foo int64
dtype: object
An easy way to tell if a string represents a valid int
is to simply attempt to convert the string to an int
and catch the ValueError
exception if it isn't a legal int
. Similarly with float
. Here's a brief demo in Python 2:
data = 'string 37 3.14159 word -5 0 -1.4142 text'
def datatype(s):
try:
int(s)
except ValueError:
try:
float(s)
except ValueError:
return 'string'
else:
return 'float'
else:
return 'int'
for s in data.split():
print '%-15r: %s' % (s, datatype(s))
output
'string' : string
'37' : int
'3.14159' : float
'word' : string
'-5' : int
'0' : int
'-1.4142' : float
'text' : string
However, normal Python code (generally) wouldn't use a function quite like that: it would assume that the data is correct and wrap the conversion code in a simple try: ... except ValueError:... else:
block rather than using that crazy nested structure to test data before you're ready to process it.
A sensible CSV won't have different datatypes in random positions, so your code shouldn't need to guess what type of data is in a give field. OTOH, not all CSV's are well-designed... :)
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