column dataframe to int
df[[column_name]].astype(int)
convert column to numeric pandas
# convert all columns of DataFrame
df = df.apply(pd.to_numeric) # convert all columns of DataFrame
# convert just columns "a" and "b"
df[["a", "b"]] = df[["a", "b"]].apply(pd.to_numeric)
convert column string to int pandas
df['DataFrame Column'] = df['DataFrame Column'].astype(int)
change dataframe column type
>>> df.astype({'col1': 'int32'}).dtypes
col1 int32
col2 int64
dtype: object
convert a pandas column to int
# convert Series
my_series = pd.to_numeric(my_series)
# convert column "a" of a DataFrame
df["a"] = pd.to_numeric(df["a"])
pandas change to numeric
>>> s = pd.Series(["8", 6, "7.5", 3, "0.9"]) # mixed string and numeric values
>>> s
0 8
1 6
2 7.5
3 3
4 0.9
dtype: object
>>> pd.to_numeric(s) # convert everything to float values
0 8.0
1 6.0
2 7.5
3 3.0
4 0.9
dtype: float64
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