If you edit files in various formats day-to-day, the universality of your document solution matters a lot. If your tools work with only a few of the popular formats, you may find yourself switching between application windows to change type in DOCM and handle other file formats. If you want to take away the headache of document editing, get a solution that will easily handle any extension.
With DocHub, you do not need to focus on anything but actual document editing. You will not have to juggle programs to work with different formats. It can help you modify your DOCM as easily as any other extension. Create DOCM documents, modify, and share them in one online editing solution that saves you time and boosts your productivity. All you need to do is sign up a free account at DocHub, which takes only a few minutes.
You will not have to become an editing multitasker with DocHub. Its feature set is enough for fast papers editing, regardless of the format you want to revise. Start by registering a free account and discover how straightforward document management might be having a tool designed particularly for your needs.
hello and welcome back to my QA video series on the pandas library in Python and the question for today is how do I change the data type of a pandas series alright lets just jump right in with an example data set so were going to import pandas as PD and then the data set were going to start with is alcohol consumption by country so drinks equals PD read CSV and then Im going to use the bitly URL bitly slash drinks by country okay so we run that lets take a look at the head and we see six columns four of which are numeric and lets actually take a look at the data types of these columns and we use the D types attribute of the drinks data frame to find that out and what we see is that three of our columns are integer columns and weve got one floating-point column the total liters column and then two columns which say type object which basically means string okay so country and continent are just strings now lets pretend for a second that we want to convert the beer servings colum
