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Data Explorer

Dynamically explore the survey's audience by picking two questions, and seeing how respondents are distributed between them.

1%
Extra Respondents
Missing Respondents
Sueldo anual
Años de experiencia
Trabajo gratis
695 respondents695
7
De 0$ a 10.000$ anuales
726 respondents726
8
De 10.000$ a 30.000$ anuales
1396 respondents1396
14
De 30.000$ a 50.000$ anuales
1957 respondents1957
20
De 50.000$ a 100.000$ anuales
2956 respondents2956
31
De 100.000$ a 200.000$ anuales
1624 respondents1624
17
Más de 200.000$ anuales
314 respondents314
3
Menos de un año
319 respondents319
3
De 1 a 2 años
1083 respondents1083
11
De 2 a 5 años
2212 respondents2212
23
De 5 a 10 años
2603 respondents2603
27
De 10 a 20 años
2796 respondents2796
29
Más de 20 años
1131 respondents1131
12
34%
27%
14%
7%
4%
0.7%
0.4%
22%
21%
24%
15%
9%
2%
0.4%
9%
11%
22%
24%
22%
8%
0.4%
3%
4%
12%
23%
36%
16%
2%
2%
2%
8%
18%
37%
24%
5%
2%
2%
5%
13%
34%
31%
8%

Extra & Missing Respondents

The chart above aims to identify areas showing higher-than-expected or lower-than-expected values compared to a calculated baseline.

For example, assuming there are 1000 CSS Grid users, and that 50% of survey respondents work in a large company, you'd expect to find 500 CSS Grid users working in large companies.

Any deviation above or below that expected total could potentially indicate an interesting correlation between both variables, and is highlighted on the chart with either colored dots (for extra respondents above the baseline) or empty dots (for missing respondents).