为什么 csv 文件中的整数作为字符串读入 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)