You can use the PandasDataFrame.astype()function to convert a column from string/int to float, you can apply this on a specific column or on an entire DataFrame. To cast the data type to a 54-bit signed float, you can usenumpy.float64,numpy.float_,float,float64as param. To cast to...
print(df.dtypes) teamobjectpoints float64 assists int64 dtype:object 请注意,points 列现在的数据类型为float64。 方法二:使用to_numeric()将对象转为浮点数 以下代码显示了如何使用to_numeric()函数将 DataFrame 中的点列从对象转换为浮点数: #convert points columnfromobjecttofloatdf['points'] = pd.to_n...
从文件读取得到的df长这样,需要转换的column是 item_price, 各个列的数据类型: 血泪史: 当试图使用astype()处理时发现报错了,错误信息是ValueError: could not convert string to float: '$2.39 ' 于是去网上查查别的转换方法,有人说使用to_numeric()可以,亲测有效,赶紧去试试看。 插播下to_numeric()的用法: ...
df['DataFrame Column'] = df['DataFrame Column'].astype(float) 在我们示例的上下文中,“DataFrame Column”是“Price”列。因此,DataFrame字符串转换为浮点数示例: import pandas as pd data = {'Product': ['ABC','XYZ'], 'Price': ['250','270'] } df = pd.DataFrame(data) df['Price'] = d...
importpandasaspd# 创建一个包含异常值的 DataFramedata={'column1':['1','two','3','4']}df=pd.DataFrame(data)# 使用 pandas 的 to_numeric 方法处理异常,将无法转换的设置为 NaNdf['column1']=pd.to_numeric(df['column1'],errors='coerce').astype(float)print(df) ...
df=pd.DataFrame(a,dtype='float')#示例1df=pd.DataFrame(data=d,dtype=np.int8)#示例2df=pd.read_csv("somefile.csv",dtype={'column_name':str}) 对于单列或者Series 下面是一个字符串Seriess的例子,它的dtype为object: 代码语言:javascript ...
# of 'Weight' column print(df.dtypes) 输出: 让我们将重量类型转换为浮点数 Python3实现 # Now we will convert it from 'int' to 'float' type # using DataFrame.astype() function df['Weight']=df['Weight'].astype(float) print()
['2016','2017','2018','2019'],'Inflation Rate':['4.47','5','5.98','4.1']}# create a dataframedf = pd.DataFrame(Data)# converting each value# of column to a stringdf['Inflation Rate'] = df['Inflation Rate'].astype(float)# show the dataframeprint(df)# show the datatypesprint(...
df = pd.DataFrame(a, dtype='float')#示例1df = pd.DataFrame(data=d, dtype=np.int8)#示例2df = pd.read_csv("somefile.csv", dtype = {'column_name': str}) 对于单列或者Series 下面是一个字符串Seriess的例子,它的dtype为object:
df.info()>><class'pandas.core.frame.DataFrame'>RangeIndex:6entries,0to5Datacolumns(total4columns):# Column Non-Null Count Dtype---0a6non-nullint641b6non-nullbool2c6non-nullfloat643d6non-nullobjectdtypes:bool(1),float64(1),int64(1),object(1)memory usage:278.0+bytes 2、转换数值类型...