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Filtering a pandas column which contains a list in other column?

I have a pandas dataframe pd like this
https://imgur.com/a/6TM3B3o
I want to filter the df_participants column which contains pd['df_pair'][0], and the expected result should be a new pd1 containing only rows that pd['df_pair'][0] is a subset of df_paticipants like this https://imgur.com/EzCcuh3
I have no idea how to do that. I have tried with .isin() or pd1 = pd[pd['df_participants'].str.contains(pd['df_pair'][0])] but it does not work. Is there any idea?

I think pd variable is not good idea for DataFrame, better is use df:
#remove nans rows
df = df.dropna(subset=['df_participants'])
#get rows if subset
df = df[df.df_participants.map(set(df['df_pair'][0]).issubset)]

python pandas: how to modify column header name and modify the date formate

Using python pandas how can we change the data frame
First, how to copy the column name down to other cell(blue)
Second, delete the row and index column(orange)
Third, modify the date formate(green)
I would appreciate any feedback~~
Update
df.iloc[1,1] = df.columns[0]
df = df.iloc[1:].reset_index(drop=True)
df.columns = df.iloc[0]
df = df.drop(df.index[0])
df = df.set_index('Date')
print(df.columns)

Question 1 - How to copy column name to a column (Edit- Rename column)
To rename a column pandas.DataFrame.rename
df.columns = ['Date','Asia Pacific Equity Fund']
# Here the list size should be 2 because you have 2 columns
# Rename using pandas pandas.DataFrame.rename
df.rename(columns = {'Asia Pacific Equity Fund':'Date',"Unnamed: 1":"Asia Pacific Equity Fund"}, inplace = True)
df.columns will return all the columns of dataframe where you can access each column name with index
Please refer Rename unnamed column pandas dataframe to change unnamed columns
Question 2 - Delete a row
# Get rows from first index
df = df.iloc[1:].reset_index()
# To remove desired rows
df.drop([0,1]).reset_index()
Question 3 - Modify the date format
current_format = '%Y-%m-%d %H:%M:%S'
desired_format = "%Y-%m-%d"
df['Date'] = pd.to_datetime(df['Date']).dt.strftime(desired_format)
# Input the existing format
df['Date'] = pd.to_datetime(df['Date'], infer_datetime_format=current_format).dt.strftime(desired_format)
# To update date format of Index
df.index = pd.to_datetime(df.index,infer_datetime_format=current_format).strftime(desired_format)
Please refer pandas.to_datetime for more details

I'm not sure I understand your questions. I mean, do you actually want to change the dataframe or how it is printed/displayed?
Indexes can be changed by using methods .set_index() or .reset_index(), or can be dropped eventually. If you just want to remove the first digit from each index (that's what I understood from the orange column), you should then create a list with the new indexes and pass it as a column to your dataframe.
Regarding the date format, it depends on what you want the changed format to become. Take a look into python datetime.
I would strongly suggest you to take a better look into pandas features and documentations, and how to handle a dataframe with this library. There is plenty of great sources a Google-search away :)

Delete the first two rows using this.
Rename the second column using this.
Work with datetime format using the datetime package. Read about it here

How do i name my index column of the attached dataset?

enter image description herePlease i am trying to name the index column but I can't. I want to be a able to name it such that I can reference it to view the index values which are dates. i have tried
df3.rename(columns={0:'Date'}, inplace=True) but it's not working.
Please can someone help me out? Thank you.

Note that the dataframe index cannot be accessed using df['Date'],
I fyou want rename the index, you can use DataFrame.rename_axis:
df=df.rename_axis(index='Date')
if you want to access it as a column then you have to transform it into a column using:
df=df.reset_index()
then you can use:
df['Date']
otherwise you can access the index by:
df.index

As there is no example data frame that you are on, I am listing an arbitrary example to demonstrate the idea.
import datetime as dt
import pandas as pd
data = {'C1' : [1, 2],
'Date' : [dt.datetime.now().strftime('%Y-%m-%d'),dt.datetime.now().strftime('%Y-%m-%d')]}
df = pd.DataFrame(data)
df.index = df["Date"]
del df["Date"]
print(df.index.name) # this will give you the new index column
print(df) #print the dataframe

how to get row number in dataframe and store as Id?

I wanna get the row number of the dataframe and store it in a new column called Id. Please advise me on how to code it.
Current dataframe:
expected outcome with new Id column:

If the first column is index use DataFrame.insert, if necessary subtract 1:
df.insert(0, 'Id', df.index - 1)
If you need count column for general solution with any index values:
df.insert(0, 'Id', np.arange(len(df)))

import pandas as pd
df = pd.DataFrame({'a':[34, 23,37,38],'b':[1,2,3,4]})
df. set_index(a, inplace=True)
Id = list(df. index)
df['Id'] = id

First, reset an index, it will add as a new column with name index. Then rename the column to the desired name
import pandas as pd
df = (df.reset_index()
.rename(columns= {'index':'ID'}
)

Need help to solve the Unnamed and to change it in dataframe in pandas

how set my indexes from "Unnamed" to the first line of my dataframe in python
import pandas as pd
df = pd.read_excel('example.xls','Day_Report',index_col=None ,skip_footer=31 ,index=False)
df = df.dropna(how='all',axis=1)
df = df.dropna(how='all')
df = df.drop(2)

To set the column names (assuming that's what you mean by "indexes") to the first row, you can use
df.columns = df.loc[0, :].values
Following that, if you want to drop the first row, you can use
df.drop(0, inplace=True)
Edit
As coldspeed correctly notes below, if the source of this is reading a CSV, then adding the skiprows=1 parameter is much better.