Python is strongly typed language, dtype=float when create DataFrame would apply to the values only making sense to be float?

Question

import pandas as pd
data = [['Alex',10],['Bob',12],['Clarke',13]]
df = pd.DataFrame(data,columns=['Name','Age'],dtype=float)
print df

When create DataFrame, we define the data type to be float, but not named which column to change to float. We leave it to python to decide if it makes sense to change the column data type or not, based on the value.

Just wondering, on this practice, is this still strict strongly typed?

Thanks!

@Take_Care_ Python is indeed dynamically typed, but it is also strongly typed. — Hamms, Jul 12 '18 at 20:48
@Hamms Yes, thank You Hamms. I didn't read the question as whole :P — Take_Care_, Jul 12 '18 at 20:52

score 3 · Accepted Answer · answered Jul 12 '18 at 20:47

Python is a strongly, dynamically typed language (see Is Python strongly typed?).

If you pass dtype=float explicitly when constructing a pd.DataFrame, Pandas will try to coerce all columns to float. In your case, the 'Name' column cannot be coerced to float, so it will remain as object (you can think of this as str in pure Python).

In general, you can leave dtype blank to have Pandas infer datatypes for DataFrames. Then do a df.info() to see if dtypes make sense to you. The ones you don't approve, you can change them like so:

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

To add to this, python _itself_ is strongly typed, which means it will never automatically perform type coercion. But Pandas is a library which explicitly provides type coercion. — Hamms, Jul 12 '18 at 20:49

Python is strongly typed language, dtype=float when create DataFrame would apply to the values only making sense to be float?

1 Answers1