在Pandas中将float64列转换为int64

大熊猫 0.24+的 解决方案，用于转换缺少值的数字：

df = pd.Dataframe({'column name':[7500000.0,7500000.0, np.nan]})print (df['column name'])0    7500000.01    7500000.02          NaNName: column name, dtype: float64df['column name'] = df['column name'].astype(np.int64)

ValueError：无法将非限定值（NA或inf）转换为整数

#http://pandas.pydata.org/pandas-docs/stable/user_guide/integer_na.htmldf['column name'] = df['column name'].astype('Int64')print (df['column name'])0    75000001    75000002        NaNName: column name, dtype: Int64

我认为您需要转换为

numpy.int64

df['column name'].astype(np.int64)

样品：

df = pd.Dataframe({'column name':[7500000.0,7500000.0]})print (df['column name'])0    7500000.01    7500000.0Name: column name, dtype: float64df['column name'] = df['column name'].astype(np.int64)#same as#df['column name'] = df['column name'].astype(pd.np.int64)print (df['column name'])0    75000001    7500000Name: column name, dtype: int64

如果某些

NaN

int

0

fillna

type

NaN

float

df = pd.Dataframe({'column name':[7500000.0,np.nan]})df['column name'] = df['column name'].fillna(0).astype(np.int64)print (df['column name'])0    75000001          0Name: column name, dtype: int64

同时检查文档-缺少数据投射规则

编辑：

用

NaN

df = pd.Dataframe({'column name':[7500000.0,np.nan]})df['column name'] = df['column name'].values.astype(np.int64)print (df['column name'])0     75000001   -9223372036854775808Name: column name, dtype: int64