39 - 列级 - df["新列名"] = 0 - 新增列和基础值

所有列后面添加新列

import numpy as np
import pandas as pd
df = pd.DataFrame(data=[{"A":"one", "B":"a"}, {"A":"two", "B":np.nan}, {"A":"one", "B":1}])

df["新列名"] = 0

不需要df_new = 返回

指定位置添加新列

df.insert(第几列用int, '新列名', 基础值int或str等)
df.insert(int, '新列名', new_value)
df.insert(df.shape[1], '新列名', new_value)  # 在最后一列加

int：指定列的列索引后面加
new_value:基础值
DataFrame信息 - df.shape[0] - [0]行数、[1]列数

import numpy as np
import pandas as pd
df = pd.DataFrame(data=[{"A":"one", "B":"a"}, {"A":"two", "B":np.nan}, {"A":"one", "B":1}])

df.insert(df.shape[1], '新列名', df['A'])

不需要df_new = 返回

df第几列用int添加

import numpy as np
import pandas as pd
df = pd.DataFrame(data=[{"A":"one", "B":"a"}, {"A":"two", "B":np.nan}, {"A":"one", "B":1}])
print(df)
df.insert(1, '新列名', df['A'])
print(df)