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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
2524 respondents2524
9
$0k-$10k
2559 respondents2559
9
$10k-$30k
4035 respondents4035
14
$30k-$50k
4905 respondents4905
17
$50k-$100k
8091 respondents8091
28
$100k-$200k
5391 respondents5391
19
Mehr als $200k
1171 respondents1171
4
Weniger als ein Jahr
1272 respondents1272
4
1 bis 2 Jahre
4177 respondents4177
15
2 bis 5 Jahre
8708 respondents8708
30
5 bis 10 Jahre
7921 respondents7921
28
10 bis 20 Jahre
5784 respondents5784
20
Mehr als 20 Jahre
2168 respondents2168
8
33%
23%
15%
8%
6%
2%
0.4%
19%
22%
22%
14%
12%
4%
0.4%
10%
11%
20%
22%
23%
10%
1%
4%
4%
11%
19%
36%
21%
4%
2%
2%
5%
12%
36%
33%
8%
3%
0.9%
3%
8%
28%
39%
14%

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).