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 ...
The to_numeric() function is used to change one or more columns in a Pandas DataFrame into a numeric object. This function converts the non-numeric values into floating-point or integer values depending on the need of the code. The following code uses the to_numeric() function to convert...
To convert a string column to an integer in a Pandas DataFrame, you can use theastype()method. To convert String to Int (Integer) from Pandas DataFrame or Series useSeries.astype(int)orpandas.to_numeric()functions. In this article, I will explain theastype()function, its syntax, parameters...
In this tutorial we will discuss how to convert DataFrame columns into int using the following methods: Convert integer type column to float: Using astype() method Using astype() method with dictionary Using astype() method by specifying data types Convert string/object type column to int Using...
# convert data type of grade column# into integerdf.grade=df.grade.astype(int)# show the dataframeprint(df)# show the datatypesprint(df.dtypes) Python Copy 输出: 方法2:使用Dataframe.apply()方法。 我们可以将pandas.to_numeric、pandas.to_datetime和pandas.to_timedelta作为参数传递给apply()函数,将...
将需要更改类型的列选取出来,假设列名为'column1'和'column2':columns_to_convert = ['column1', 'column2'] 使用to_datetime()函数将选定的列转换为日期格式,并指定格式为'%Y-%m-%d':df[columns_to_convert] = df[columns_to_convert].apply(pd.to_datetime, format='%Y-%m-%d') ...
pandas中有种非常便利的方法to_numeric()可以将其它数据类型转换为数值类型。 pandas.to_numeric(arg, errors='raise', downcast=None) arg:被转换的变量,格式可以是list,tuple,1-d array,Series errors:转换时遇到错误的设置,ignore,raise,coerce,下面例子中具体讲解 ...
df['mix_col'] = pd.to_numeric(df['mix_col'], errors='coerce') df output 而要是遇到缺失值的时候,进行数据类型转换的过程中也一样会出现报错,代码如下 df['missing_col'].astype('int') output ValueError: Cannot convert non-finite values (NA or inf) to integer ...
pandas.to numeric() 是在 Pandas 中将参数转换为数字形式的广泛使用的方法之一。 范例1: Python3 # import pandas libraryimportpandasaspd# dictionaryData = {'Name':['GeeksForGeeks','Python'],'Unique ID':['900','450']}# create a dataframe objectdf = pd.DataFrame(Data)# convert integer to str...
运行上述代码,结果程序抛出异常:IntCastingNaNError: Cannot convert non-finite values (NA or inf) to integer,这个异常告诉我们 Pandas 中的空值 NaN 不可以被转为整数,实际上正是如此,NaN 的类型是 float,缺失无法被转为整数型,所以转换不会成功,程序自然就会报错。