Why Integers in csv file read as strings into pandas dataframe

Question

In the following csv file, some columns contain data with different datatypes, ie some rows are integers and some rows are strings.

"ip_v", "ittl", "olen", "mss",  "OS_type"
 "*",    64,       0,     "*",   "Windows"
  4,     64,       0,    1430,   "Linux"
 "*",   "64-",     0,    1460,   "MAC-OS"

I read the csv file into pandas dataframe
df = pd.read_csv("file.csv")
And iterate through each row in a for loop and check the type of each value to proceed further.
But, though the values types are different in csv file, in python all values are read as strings . For example, when I check the type for "ittl" column values in each row, they all read as string but I was expecting row 0 and 1 to be int and row 2 to be str .
Why am I facing this problem, what is going on?

for index, row in df.iterrows():
    print(row['ittl'], type(row['ittl']))

Output:
64    <class 'str'>
64    <class 'str'>
64-   <class 'str'>

Answer 1

i dont know but if you want to make your column as an int type you can make this:

df['ittl'] = df['ittl'].astype(int)