Accessing first column of pandas value_counts

Question

I'm trying to use value_counts() function from Python's pandas package to find the frequency of items in a column. This works and outputs the following:

57     1811
62      630
71      613
53      217
59      185
68       88
52       70

Name: hospitalized, dtype: int64

In which the first column is the item and the right column is its frequency in the column.

From there, I wanted to access the first column of items and iterate through that in a for loop. I want to be able to access the item of each row and check if it is equal to another value. If this is true, I want to be able to access the second column and divide it by another number.

My big issue is accessing the first column from the .value_counts() output. Is it possible to access this column and if so, how? The columns aren't named anything specific (since it's just the value_counts() output) so I'm unsure how to access them.

Answer 1

Use Panda's iteritems():

df = pd.DataFrame({'mycolumn': [1,2,2,2,3,3,4]})
for val, cnt in df.mycolumn.value_counts().iteritems():
    print 'value', val, 'was found', cnt, 'times'

value 2 was found 3 times
value 3 was found 2 times
value 4 was found 1 times
value 1 was found 1 times

Answer 2

value_counts returns a Pandas Series:

df = pd.DataFrame(np.random.choice(list("abc"), size=10), columns = ["X"])
df["X"].value_counts()
Out[243]: 
c    4
b    3
a    3
Name: X, dtype: int64

For the array of individual values, you can use the index of the Series:

vl_list = df["X"].value_counts().index
Index(['c', 'b', 'a'], dtype='object')

It is of type "Index" but you can iterate over it:

for idx in vl_list:
    print(idx)

c
b
a

Or for the numpy array, you can use df["X"].value_counts().index.values

Answer 3

You can access the first column by using .keys() or index as below:

df.column_name.value_counts().keys()

df.column_name.value_counts().index