Best open source data visualization software to use with PowerPoint What is the best open source data visualization software? I require the following:


*

*Can import data from Microsoft Excel (importing data from Oracle databases would be good too, but this is not mandatory).

*Charts generated by the software can be exported to Microsoft PowerPoint (copy and paste is fine with me).

*Open source & easy to use.
 A: Updated 2017-02-24:
I think that the best solutions is to use R with RStudio.  ( Python and iPython notebook is an alternative ):


*

*Data import


*

*Excel: readxl package 

*Oracle: ora or RODBC package


*Plotting: ggplot2

*Exporting plots 


*

*Copy-and-paste: RStudio's exports plot functionality

*Programatically: ReporteRs package



TLDR;
Data Import
There are numerous ways to import excel (tabular) data. For Excel data, the readxl package provides the easiest and most versatile. It generally gets the variable types correct on import.  
Alternatives are to save the file as CSV and re-import. The readr package is good for this. @Nick Stauner provides perhaps the most basic solution using read.csv; the limitation is that this requires the additional step of saving a worksheet as a CSV file.  This is not great if your data is spread across multiple sheets.  It can get tedious though there are VBA programs for saving all sheets as CSV files. Google for them. Another limitation is getting the types of the variables correct.  If you use read.csv, you often have to fix your types after importing in R.  
There are a few packages that avoid these problems by allowing you to connect read/write  from the spreadsheet directly or by using ODBC.  Search on CRAN for excel or odbc to find the relevant one for your situation.
Plotting
In terms of getting plots into powerpoint, use Rstudio's export plot functions, the copy and paste method using Rstudio is:
export plot > copy plot to clipboard > copy as:  metafile captures the plot to the the paste buffer allowing you to paste directly into Power Point.
As far as generating plots, R has numerous options. The aforementioned ggplot2 package provides a very powerful interface for creating all sorts of plots.  There are additional packages for doing hundreds or thousands of other types of plots/animations/etc.  One limitation is that these are often buried in CRAN packages. 
An alternative is to use the ReporteRs package.
A: I agree with Nick Stauner on R. And, with a username like "R Learner" I was tempted to not suggest other tools, but there are many. I'll wait to see what the answer to my questions are for more platform-specific ones, but Mondrian is a Java desktop program (so cross-platform) and supports many visualization types that you can easily get into PowerPoint.
A: I don't know about "best", but the software environment you're named after fits all your requirements:


*

*I keep my data in Excel spreadsheets; when I'm ready to import them to R, I save as CSV and use read.csv(). 


*

*The RODBC and ora packages are available for importing from Oracle. 


*Images produced in R can be copied as bitmaps or metafiles and pasted directly into PowerPoint. You can find plenty of recommendations here for R as an open-source data visualization utility:


*

*Open source tools for visualizing multi-dimensional data?

*Does anyone know any good open source software for visualizing data from database?

*Software for easy-yet-robust data exploration

*Resources for learning to create data visualizations?

*Resources for learning to use (/create) dynamic (/interactive) statistical visualization


*

*R: update a graph dynamically!


*How can I create nice graphs automatically?

*Web visualization libraries

*Free treemapping software

*Recommended visualization libraries for standalone applications

*Other suggestions in these threads are worth considering too, but I haven't tried them.

*More enthusiasm about R in general (not just for data visualization):


*

*What are some valuable Statistical Analysis open source projects?

*What is your favorite, easy to use statistical analysis website or software package?

*vs. Python as a statistics workbench ... a close contest at least!



*R is open-source. Though its learning curve is nontrivial, it becomes easy to use with experience.

