Q:

Selecting rows from pandas DataFrame using a list

I have a list of lists as below 
[[1, 2], [1, 3]]

The DataFrame is similar to 
  A B C
0 1 2 4
1 0 1 2
2 1 3 0

I would like a DataFrame, if the value in column A is equal to the first element of any of the nested lists and the value in column B of the corresponding row is equal to the second element of that same nested list.
Thus the resulting DataFrame should be
  A B C
0 1 2 4
2 1 3 0

A:

The code below do want you need:
tmp_filter = pandas.DataFrame(None) #The dataframe you want
# Create your list and your dataframe
tmp_list = [[1, 2], [1, 3]]
tmp_df = pandas.DataFrame([[1,2,4],[0,1,2],[1,3,0]], columns = ['A','B','C'])

#This function will pass the df pass columns by columns and
#only keep the columns with the value you want
def pass_true_df(df, cond):
    for i, c in enumerate(cond):
        df = df[df.iloc[:,i] == c]
    return df

# Pass through your list and add the row you want to keep
for i in tmp_list:
    tmp_filter = pandas.concat([tmp_filter, pass_true_df(tmp_df, i)])

