df['myvar'] = df['myvar'].astype(str) # Transform as character
df['myvar'] = df['myvar'].astype(float) # Transform as float
df['myvar'] = df['myvar'].astype(int) # Transform as numeric>>> df.astype({'col1': 'int32'}).dtypes
col1 int32
col2 int64
dtype: object# convert Series
my_series = pd.to_numeric(my_series)
# convert column "a" of a DataFrame
df["a"] = pd.to_numeric(df["a"])
>>> 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
# select columns that need to be converted
cols = df.select_dtypes(include=['float64']).columns.to_list()
df = df.astype({col:int for col in cols})df.astype(int)