根据列表熊猫在数据框中插入命名行

Question

I have a list (lets call it Y) of names and it's size is (1080,1). I also have a dataframe of size(700,20) ( lets call it X) with the index containing names from the list Y. That is, there is no names in the dataframe that are not contained in Y, but there are names in Y that are not contained in the dataframe. Now what I would like to do is to insert empty rows containing the names in Y that are not already in X. Hence, I would like to add 380 new rows with empty values in all the columns and index values equal to the values of Y not already contained in the dataframe.

Answer 1

What about this:

import pandas as pd
import numpy as np
df1 = pd.DataFrame({"name":["Marc", "Eric", "Bob"], "x":np.arange(3)})
Y = ["Marc", "Eric", "Bob","Carl"]
df2 = pd.DataFrame({"name":Y})
df = pd.concat([df1, df2[~df2["name"].isin(df1["name"])]])

Update I slightly modified my example to suit your case (except for first 4 characters instead of 10)

import pandas as pd
import numpy as np
df1 = pd.DataFrame({"name":["Marc Green", "Eric White", "Carl Red"], "x":np.arange(3)})
Y = ["Marc", "Eric", "Anna","Carl"]
df2 = pd.DataFrame({"name":Y})
df = pd.concat([df1, df2[~df2["name"].isin(df1["name"].str[:4])]])

Update 2 It seems that in your case names in dataframe X are - separated so you can use this solution

df1 = pd.DataFrame({"name":["Marc - Green", "Eric - White", "Carl - Red"], "x":np.arange(3)})
Y = ["Marc", "Eric", "Anna","Carl"]
df2 = pd.DataFrame({"name":Y})
df = pd.concat([df1, df2[~df2["name"].isin(df1["name"].str.split("-").apply(lambda x:x[0].strip()))]])

Note as others already commented, when you ask a question is better if you provide an example of your data in text format so it's easy for other to help.