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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
Jährliches Einkommen
Erfahrung in Jahren
Ich arbeite kostenlos
695 respondents695
7
$0k-$10k
726 respondents726
8
$10k-$30k
1396 respondents1396
14
$30k-$50k
1957 respondents1957
20
$50k-$100k
2956 respondents2956
31
$100k-$200k
1624 respondents1624
17
Mehr als $200k
314 respondents314
3
Weniger als ein Jahr
319 respondents319
3
1 bis 2 Jahre
1083 respondents1083
11
2 bis 5 Jahre
2212 respondents2212
23
5 bis 10 Jahre
2603 respondents2603
27
10 bis 20 Jahre
2796 respondents2796
29
Mehr als 20 Jahre
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).