Check if ENTIRE pandas object column is a string

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How can I check if a column is a string, or another type (e.g. int or float), even though the dtype is object?

(Ideally I want this operation vectorised, and not applymap checking every row...)

import io
# American post code
df1_str = """id,postal
1,12345
2,90210
3,"""
df1 = pd.read_csv(io.StringIO(df1_str))
df1["postal"] = df1["postal"].astype("O")  # is an object (of type float due to the null row 3)

# British post codes
df2_str = """id,postal
1,EC1
2,SE1
3,W2"""
df2 = pd.read_csv(io.StringIO(df2_str))
df2["postal"] = df2["postal"].astype("O")  # is an object (of type string)

Both df1 and df2 return object when doing df["postal"].dtype

  • However, df2 has .str methods, e.g. df2["postal"].str.lower(), but df1 doesn't.
  • Similarly, df1 can have mathematical operations done to it, e.g. df1 * 2

This is different to other SO questions. who ask if there are strings inside a column (and not the WHOLE column). e.g:

pandas python
1 Answers

You can use pandas.api.types.infer_dtype:

>>> pd.api.types.infer_dtype(df2["postal"])
'string'
>>> pd.api.types.infer_dtype(df1["postal"])
'floating'

From the docs:

Efficiently infer the type of a passed val, or list-like array of values. Return a string describing the type.

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