def wrapper(row): return get_circumcircle_area(row['Length'],row['Height']) rects = pd.read_excel('E:/pandas/pad/biaoge/Students.xlsx',index_col='ID') rects['CA']=rects.apply(wrapper,axis=1) print(rects) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. import pandas as pd im...
with_row_count("rn") print(df) out = df.select(pl.col("*")) # Is equivalent to out = df.select(pl.all()) print(out) out = df.select(pl.col("*").exclude("logged_at", "rn")) print(out) out = df.select(pl.col("date", "logged_at").dt.to_string("%Y-%h-%d")) ...
这里只指定了列名为ID,Name,Gender和Birthdate,使用names函数可以查看列名,如果要查看行名,需要用到row.names函数。这里我们希望将ID作为行名,那么可以这样写: row.names(student)<-student$ID 1. 更简单的办法是在初始化date.frame的时候,有参数row.names可以设置行名的向量。 访问元素 与Matrix一样,使用[行In...
方法描述Axesindex: row labels;columns: column labelsDataFrame.as_matrix([columns])转换为矩阵DataFrame.dtypes返回数据的类型DataFrame.ftypesReturn the ftypes (indication of sparse/dense and dtype) in this object.DataFrame.get_dtype_counts()返回数据框数据类型的个数DataFrame.get_ftype_counts()Return th...
pd.concat()参数(objs, axis=0, join='outer', join_axes=None, ignore_index=False, keys=None, levels=None, names=None, verify_integrity=False, sort=None, copy=True) axis=0 列方向级联拼接,axis=1行方向级联拼接,默认为0 join为级联方式,outer会将所有的项进行级联(忽略匹配和不匹配),取并集,而...
(student$Gender=="F"),] #首先对student$Gender==“F”,得到一个布尔向量:FALSE FALSE TRUE,然后使用which函数可以将布尔向量中TRUE的Index返回 student[which(student$Gender=="F"),"Age"] #查询所有女性的年龄 #直接使用subset函数查询 subset(student,Gender=="F" & Age<30 ,select=c("Name","Age")...
num=10000start=time.perf_counter()df=pd.DataFrame({"seq":[]})foriinrange(row_num):df1=pd....
DataFrame.select(crit[, axis])Return data corresponding to axis labels matching criteria DataFrame.set_index(keys[, drop, append, …])Set the DataFrame index (row labels) using one or more existing columns. DataFrame.tail([n])返回最后几行 ...
index Returns the row labels of the DataFrame infer_objects() Change the dtype of the columns in the DataFrame info() Prints information about the DataFrame insert() Insert a column in the DataFrame interpolate() Replaces not-a-number values with the interpolated method isin() Returns True if...
df.Column(int columnIndex, NDArray value): Set the column and the value of the column; when the column does not exist, an exception is reported df[Slice s]: Row slice selection data df.loc["index_label"]: Select data by row index label ...