If you have a DataFrame with all string columns holding integer values, you can simply convert it to int dtype using as below. If you have any column that has alpha-numeric values, this returns an error. If you run this on our DataFrame, you will get an error. # Convert all columns ...
# using dictionary to convert specific columns convert_dict={'A':int, 'C':float} df=df.astype(convert_dict) print(df.dtypes) 输出: 注:本文由VeryToolz翻译自Convert the data type of Pandas column to int,非经特殊声明,文中代码和图片版权归原作者vaishalianand1276所有,本译文的传播和使用请遵循“...
Convert to int using convert_dtypes() Create pandas DataFrame with example data DataFrame is a data structure used to store the data in two dimensional format. It is similar to table that stores the data in rows and columns. Rows represents the records/ tuples and columns refers to the attr...
The to_numeric() function can be used to convert multiple columns of a DataFrame as well as using the apply() method. The following code implements the to_numeric() function to convert the datatype of all the columns to int. 1 2 3 4 5 6 7 8 import pandas as pd df = pd.DataFra...
Python Copy 输出: 现在,我们将列 “B “的数据类型转换成 “int “类型。 # using apply methoddf[['B']]=df[['B']].apply(pd.to_numeric)# show the data types# of all columnsdf.dtypes Python Copy 输出:
df.Fee = df['Fee'].astype('int') print(df.dtypes) # Output: # Courses object # Fee int32 # Duration object # Discount object # dtype: object Multiple Columns Integer Conversion Alternatively, to convert multiple string columns to integers in a Pandas DataFrame, you can use theastype()me...
RangeIndex: 4 entries, 0 to 3 Data columns (total 8 columns): # Column Non-Null Count Dtype --- --- --- --- 0 string_col 4 non-null object 1 int_col 4 non-null int64 2 float_col 4 non-null float64 3 mix_col 4 non-null ...
df=pd.DataFrame({'a':[1,2]*3,'b':[True,False]*3,'c':[1.0,2.0]*3,'d':['a','b']*3})# 筛选float和int的数值类型变量 num_list=df.select_dtypes(include=['float','int64']).columns.tolist()# 筛选ojbect字符型的数值类型变量 ...
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在pandas 1.0 中,引入了一种新的转换方法.convert_dtypes。它会尝试将Series 换为支持 pd.NA 类型。以city_mpg 系列为例,它将把类型从int64转换为Int64: >>>city_mpg.convert_dtypes()01919223310417..41139194114020411411841142184114316Name: city08, Length:41144, dtype: Int64>>>city_mpg.astype('Int16')019...