General recommendation
Before constructing any display of epidemiologic data, it is important to first determine the point to be conveyed. Are you highlighting a change from past patterns in the data? Are you showing a difference in incidence by geographic area or by some predetermined risk factor? What is the interpretation you want he reader to reach? Your answer to these questions will help to determine the choice of display [1].
As a general recommendation, use a table for precise numbers, for large amounts of numbers, and if there is a great range between the largest and smallest figures. Use a graph for showing trends and relationships, displaying changes over time, and for explaining a point vividly. Use either a table or a graph for comparisons, and for showing parts of a whole [2].
Often the choice between presenting data in a table or graph is arbitrary as both will work. In general when presenting lots of data e.g. in an annual report it is best to vary how the data is presented by making use of both tables and graphs. A graphical presentation of data has the advantage of enabling a person to visualise a relationship between data i.e. proportions in groups. There is also a subjective nature to this as some individuals find it easier to interpret tables while others find a visual representation more easy to interpret.
If you decide that a graph is the best way to present your information, then no matter what type of graph you use, you need to keep in mind the following 10 tips [3]:
 convey an important message
 decide on a clear purpose
 draw attention to the message, not the source
 experiment with various options and graph styles
 use simple design for complex data
 make the data 'speak'
 adapt graph presentation to suit the target audience
 ensure that the visual perception process is easy and accurate
 avoid distortion and ambiguity
 optimize design and integrate style with text and tables
Describing one variable
The first step is to describe one variable which is crucial before one starts to compare two or more variables. The table below summarises the most common presentation formats for the different types of variables, from the "simplest" to the more "complex".
Describing ONE variable 
Variable 
Aims 
Table 
Graph 
Binary / dichotomous 
Describe with proportions 
Frequency distribution table 
Bar graph, Pie graph 
Nominal (categorical not ordered) 
Describe with proportions 
Frequency distribution table 
Bar graph, Pie graph 
Ordinal (categorical (ordered) 
Describe with proportions 
Frequency distribution table (also cumulative) 
Bar graph(also cumulative), Pie graph 
Numerical discrete 
Describe with proportions, means and standard deviation 
Frequency distribution table (also cumulative), Table of descriptive statistics 
Bar graph (also cumulative), Histogram (if large number of values)

Numerical continuous 
Describe with means, medians, standard deviation, quartiles 
Frequency distribution table (group frequencies or cumulative), Table of descriptive statistics 
Histogram (also cumulative), Frequency polygon, Boxandwhisker plot, Violin plot, Oneway scatter plot 
Describing two variables together
There are potentially 5x5 = 25 combinations of the types of variables mentioned in the table above; there are many potential graphs and tables to describe these. The important thing is that you understand what you wants to show in those tables or graphs. For describing two variables (X and Y) together the strategy is basically the following:
First, consider one variable as the "outcome" (Y) and the other as the "factor" (X), i.e. explanatory variable. Then describe the outcome (Y) in each group that you can make with the factor (X). Remember that the outcome will be described according to its nature as explained above (univariate description).
Below you find a simple summary of describing two variables together.
Describing TWO variables together 
Variable 
Aims 
Table 
Graph 
Two categorical variables 
Identify relationships, patterns in the data 
Contingency table 
Grouped bar graph, Stacked bar graph, Component bar graph, Mosaic plot 
Two numerical variables 
Contingency table (group frequencies) 
Line graph (also cumulative), Scatter plot (with or without regression line) 
One categorical and one numerical variable 
Contingency table, Table of descriptive statistics (mean, median, mode, etc) 
Scatter plot, Boxandwhisker plot, Bar graph (showing mean or median with ± standard deviation) 
There are typical table formats for presenting results of cohort and casecontrol studies.
Time series
Time series is a special case of describing two variables where the factor (X) variable is always the "time". Selecting a method of displaying time series data is based on certain conditions [4].
References
1. U.S. Dept. of Health and Human Services  Centers for Disease Control and Prevention (CDC). Selfstudy course 3030G. Principles of epidemiology. An introduction to applied epidemiology and biostatistics. 2nd ed.
2. Bigwood S, Spore M. Presenting numbers, tables and charts. Oxford University Press, New York, 2003 p. 84
3. Statistics Canada, Statistics: Power from data!  Summary
4. U.S. Dept. of Health and Human Services  Centers for Disease Control and Prevention (CDC). Selfstudy course 3030G. Principles of epidemiology. An introduction to applied epidemiology and biostatistics. 2nd ed. p. 264