Find columns with numeric values, but stored as string

Question

I need to find the columns in data frame, which has numeric values and are stored as string.

data_set = pd.DataFrame({"Number":["1","2","3","4","5"], "Char":["A","B","C","D","E"]})
data_set.dtypes

In above code, column "Number" has numeric values, but stored as string. I have to iterate through columns and convert it to int or float.

I can do it by taking column name and convert it.

data_set["Number"] = data_set["Number"].astype(int)

What i need is to do it dynamically. Dynamically means, iterating through columns and changing it.

Answer 1

I think this does what you want.

for column in data_set:
    If isinstace(data_set[column].dtypes,str)
        data_set[column]=data_set[column].astype(int)

Answer 2

I put together the following code but I don't claim it to be the best option:

for col in data_set.columns:
    for element in data_set[col]:
        if element.isdigit():
            data_set[col] = data_set[col].astype(int)

Please note, that this code will try to convert the whole column to int, if there is a single entry of an int-value stored as string. So it might return an error for mixed type columns.