Example 1: Append New Variable to pandas DataFrame Using assign() Function Example 1 illustrates how to join a new column to a pandas DataFrame using the assign function in Python. Have a look at the Python syntax below: data_new1=data.assign(new_col=new_col)# Add new columnprint(data_...
The second line specifies what we want to do in this loop, i.e. in each iteration we want to add a new column containing the iterator i times the value three. The variable name of this new column should be called like the iterator. ...
df['Chemistry'] # Returns column with label 'Chemistry' as Series 1. df[['Name','Algebra']] # Returns columns as a new DataFrame 1. df.iloc[0] # Selection by position 1. df.iloc[:,1] # Second column 'Name' of data frame 1. df.iloc[0,1] # First element of Second column >...
DataFrame.lookup(row_labels, col_labels)Label-based “fancy indexing” function for DataFrame. DataFrame.pop(item)返回删除的项目 DataFrame.tail([n])返回最后n行 DataFrame.xs(key[, axis, level, drop_level])Returns a cross-section (row(s) or column(s)) from the Series/DataFrame. DataFrame.is...
Merge DataFrame or named Series objects with a database-style join. The join is done on columns or indexes. If joining columns on columns, the DataFrame indexeswill be ignored. Otherwise if joining indexes on indexes or indexes on a column or columns, the index will be passed on. ...
一般要求两个DataFrame的形状相同,如果不同,会出现NaN的值。 DataFrame运算可以直接使用运算符,也可以使用对应的方法,支持的运算有: 运算方法 运算说明 df.add(other) 对应元素的加,如果是标量,就每个元素加上标量 df.radd(other) 等效于other+df df.sub(other) 对应元素相减,如果是标量,就每个元素减去标量 df....
df['column3'] = df.apply(apply_fx, axis=1) 以下我們用一個簡單例子開始解說 pandas apply。 簡單例子:透過 pandas apply 計算 BMI 匯入pandas 並定義 df。 我們用一個簡單的體重/身高 dataframe 示範如何計算 BMI。 import pandas as pd df = pd.DataFrame( ...
df.info() <class 'pandas.core.frame.DataFrame'> RangeIndex: 6040 entries, 0 to 6039 Data columns (total 5 columns): UserID 6040 non-null int64 Gender 6040 non-null object Age 6040 non-null int64 Occupation 6040 non-null int64 Zip-code 6040 non-null object dtypes: int64(3), object(2...
lastEle = df.loc[df.index[-1],column_name] ③访问某一列 df.列名或df['列名']的方式访问某一列 该方式只能访问一列,如果要访问多列请用上文①②讲的方法。 2.5.3、返回DataFrame的array形式:values 返回值类型为numpy.ndarray 只返回DataFrame中的值,而不返回label行和列。
以下是一些常见的数据选择和过滤操作示例：# 选择单个列name_column=df['Name']# 选择多个列subset=df...