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: >>> s = pd.Series(['1','2','4.7','pandas','10...
语法: df[“column_name”] = np.where(df[“column_name”]==”some_value”, value_if_true, value_if_false) 例子:在此示例中,代码导入Pandas和NumPy库,从包含学生数据的名为“student”的字典中构建名为“df”的DataFrame,并使用NumPy np.where函数将“gender”列的值从“female”更改为“0”,将“mal...
import pandas as pd def test(): # 读取Excel文件 df = pd.read_excel('测试数据.xlsx') # 插入列 df.insert(loc=2, column='爱好', value=None) # 保存修改后的DataFrame到新的Excel文件 df.to_excel('结果.xlsx', index=False) test() 3、插入多列 假设我需要在D列(班级)后面插入5列,表头名...
df.rename(columns={'old_name':'new_ name'}) # 选择性更改列名 df.set_index('column_one') # 将某个字段设为索引,可接受列表参数,即设置多个索引 df.reset_index("col1") # 将索引设置为col1字段,并将索引新设置为0,1,2... df.rename(index=lambdax:x+1) # 批量重命名索引 6.数据分组、排...
print(df) 运行以上代码后,将创建一个带有行名和列名的DataFrame,输出结果应该如下(注意,原输出示例中存在格式错误,以下输出已修正): Column1 Column2 Row1 1 4 Row2 2 5 Row3 3 6 在这个例子中,我们创建了一个包含两列(’Column1’和’Column2’)和三行(’Row1’、’Row2’和’Row3’)的DataFrame。
1. DF= DF.drop('column_name', axis=1); 2. DF.drop('column_name',axis=1, inplace=True) 3. DF.drop([DF.columns[[0,1, 3]]], axis=1, inplace=True) 注意:凡是会对原数组作出修改并返回一个新数组的,往往都有一个 inplace可选参数。如果手动设定为True(默认为False),那么原数组直接就...
If you already have a DataFrame and want to change the column names, you can directly assign a new list of column names to thecolumnsattribute of the DataFrame. How can I add a new column to an existing DataFrame with a specific name and values?
You can change the position of a Pandas column using the df.reindex() function bychanging the order of Pandas column’sposition in the desired order. For example, first, specify the order of the column’s position and pass it into the reindex() function, it will change the column’s pos...
Now, with that DataFrame object, we have used theadd.prefix()method to change the column name. The add_prefix() will add a specific string at the beginning of all the column names. We put the entire operation under the print() function to display the result. ...
df = pd.read_csv('data.csv') print(df) 1. 2. 注意:这里假设data.csv文件与Python脚本在同一目录下,且文件内容格式正确。 三、行与列的基本操作 1. 选择行与列 选择单列: print(df['Name']) 1. 输出结果: 0 Alice 1 Bob 2 Charlie