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 numericchange dataframe column type
>>> df.astype({'col1': 'int32'}).dtypes
col1 int32
col2 int64
dtype: objectconvert 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: float64set column datatype pandas
df = pd.read_csv("weather.tsv", sep="\t",
dtype={'Day': str,'Wind':int64})
df.dtypesCopyright © 2021 Codeinu
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