python: transform as type numeirc
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 numericpython: transform as type numeirc
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 numericpandas 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: float64python cast to int
x = int(1) # x will be 1
y = int(2.8) # y will be 2
z = int("3") # z will be 3Copyright © 2021 Codeinu
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