The function match works on vectors: match only returns the first encounter of a match, as you requested. It returns the position in the second argument of the values in the first argument. For multiple matching, %in% is the way to go: %in% returns a logical vector as long as the first argument, with a … Read more
Your output variable is not a N x 4 matrix, at least not in python types sense. It is a tuple, which can only be indexed by a single number, and you try to index by tuple (2 numbers with coma in between), which works only for numpy matrices. Print your output, figure out if … Read more
Does this include: International numbers? Extensions? Other information besides the actual number (like “ask for bobby”)? If all of these are no, I would use a 10 char field and strip out all non-numeric data. If the first is a yes and the other two are no, I’d use two varchar(50) fields, one for the … Read more
df.iloc[i] returns the ith row of df. i does not refer to the index label, i is a 0-based index. In contrast, the attribute index returns actual index labels, not numeric row-indices: or equivalently, You can see the difference quite clearly by playing with a DataFrame with a non-default index that does not equal to the row’s numerical position: If you want to use the index, … Read more
df.iloc[i] returns the ith row of df. i does not refer to the index label, i is a 0-based index. In contrast, the attribute index returns actual index labels, not numeric row-indices: or equivalently, You can see the difference quite clearly by playing with a DataFrame with a non-default index that does not equal to the row’s numerical position: If you want to use the index, … Read more
An index is used to speed up searching in the database. MySQL have some good documentation on the subject (which is relevant for other SQL servers as well): http://dev.mysql.com/doc/refman/5.0/en/mysql-indexes.html An index can be used to efficiently find all rows matching some column in your query and then walk through only that subset of the table to … Read more