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)pandas decimal places
# (1) Round to specific decimal places – Single DataFrame column
df['DataFrame column'].round(decimals=number of decimal places needed)
# (2) Round up – Single DataFrame column
df['DataFrame column'].apply(np.ceil)
# (3) Round down – Single DataFrame column
df['DataFrame column'].apply(np.floor)
# (4) Round to specific decimals places – Entire DataFrame
df.round(decimals=number of decimal places needed)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: float64Copyright © 2021 Codeinu
Forgot your account's password or having trouble logging into your Account? Don't worry, we'll help you to get back your account. Enter your email address and we'll send you a recovery link to reset your password. If you are experiencing problems resetting your password contact us
