Convert Column to Int (Integer) You can use pandasDataFrame.astype()function to convert column to int(integer). You can apply this to a specific column or to an entire DataFrame. To cast the data type to a 64-bi
Method 5 : Convert string/object type column to int using astype() method with dictionary Method 6 : Convert string/object type column to int using astype() method by specifying data types Method 7 : Convert to int using convert_dtypes() Summary References Different methods to convert...
0to1Datacolumns(total3columns):# Column Non-Null Count Dtype---0year2non-nullint641month2non-nullobject2day2non-nullint64dtypes:int64(2),object(1)memory usage:176.0+bytes 此外这里再延伸一下,去掉
y object dtype: object After using to_numeric() function x int64 y int64 dtype: object In the above code, the apply() function is used along with the to_numeric() function on the given DataFrame to convert multiple columns into int at once. Further reading: Pandas convert column to flo...
国家object 受欢迎度 int64 评分float64 向往度 float64dtype:object 可以看到国家字段是object类型,受欢迎度是int整数类型,评分与向往度都是float浮点数类型。而实际上,对于向往度我们可能需要的是int整数类型,国家字段是string字符串类型。 那么,我们可以在加载数据的时候通过参数dtype指定各字段数据类型。
使用convert_dtypes().dtypes函数进行转换 示例: importpandasaspdimportnumpyasnp# Creating the Data frame through series# and specifying datatype along with itdf=pd.DataFrame({"Column_1":pd.Series([1,2,3],dtype=np.dtype("int32")),# Column_1 datatype is int32"Column_2":pd.Series(["Apple...
To convert a string column to an integer in a Pandas DataFrame, you can use the astype() method. To convert String to Int (Integer) from Pandas DataFrame
df.dtypescol1int64col2int64dtype:object 要强制使用单个dtype：df=pd.DataFrame(data=d,dtype=np.in...
Int Float Object Boolean DatetimeConverting entire pandas dataframe to integersAll these data types can be converted into some other data types using the astype() method. This method is used when we want to convert the data type of one single column or a series, but if we want to convert ...
Convert an Object-Type Column to Float in Pandas An object-type column contains a string or a mix of other types, whereas a float contains decimal values. We will work on the following DataFrame in this article. importpandasaspd df=pd.DataFrame([["10.0",6,7,8],["1.0",9,12,14],["...