# SparseArray cannot store arbitrary type, but only types which support zero
**URL:** https://discourse.julialang.org/t/sparsearray-cannot-store-arbitrary-type-but-only-types-which-support-zero/64283
**Category:** General Usage
**Tags:** question
**Created:** [July 8, 2021, 3:24pm UTC](https://discourse.julialang.org/t/sparsearray-cannot-store-arbitrary-type-but-only-types-which-support-zero/64283 "2021-07-08T15:24:18Z")
**Posts on this page:** 7
**Page:** 1
### Author:  [@schlichtanders](https://discourse.julialang.org/u/schlichtanders)
#### Post date: [July 8, 2021, 3:24pm UTC](https://discourse.julialang.org/t/sparsearray-cannot-store-arbitrary-type-but-only-types-which-support-zero/64283/1 "2021-07-08T15:24:18Z")
I think this is a bug report to Julia, however I first would like to gather some thoughts.
Concretely, I cannot map over a SparseVector of Functions.
```julia
julia> a = SparseVector([1, 2])
2-element SparseVector{Int64, Int64} with 2 stored entries:
[1] = 1
[2] = 2
julia> fs = map(x -> y -> x+y, a)
2-element SparseVector{var"#32#34"{Int64}, Int64} with 2 stored entries:
[1] = #32
[2] = #32
julia> map(f -> f(1), fs)
ERROR: MethodError: no method matching zero(::Type{var"#32#34"{Int64}})
Closest candidates are:
zero(::Union{Type{P}, P}) where P<:Dates.Period at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.6/Dates/src/periods.jl:53
zero(::T) where T<:Dates.TimeType at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.6/Dates/src/types.jl:423
zero(::AbstractIrrational) at irrationals.jl:148
...
Stacktrace:
[1] _zeros_eltypes
@ /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.6/SparseArrays/src/higherorderfns.jl:204 [inlined]
[2] _noshapecheck_map(::var"#35#36", ::SparseVector{var"#32#34"{Int64}, Int64})
@ SparseArrays.HigherOrderFns /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.6/SparseArrays/src/higherorderfns.jl:160
[3] map(f::var"#35#36", A::SparseVector{var"#32#34"{Int64}, Int64})
@ SparseArrays.HigherOrderFns /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.6/SparseArrays/src/higherorderfns.jl:143
[4] top-level scope
@ REPL[96]:1
```
Using julia 1.6.1
```julia
julia> versioninfo()
Julia Version 1.6.1
Commit 6aaedecc44 (2021-04-23 05:59 UTC)
Platform Info:
OS: Linux (x86_64-pc-linux-gnu)
CPU: Intel(R) Core(TM) i7-1065G7 CPU @ 1.30GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-11.0.1 (ORCJIT, icelake-client)
Environment:
JULIA_EDITOR = code-insiders
JULIA_NUM_THREADS =
```
---
### Author:  [@roflmaostc](https://discourse.julialang.org/u/roflmaostc)
#### Post date: [July 8, 2021, 3:35pm UTC](https://discourse.julialang.org/t/sparsearray-cannot-store-arbitrary-type-but-only-types-which-support-zero/64283/2 "2021-07-08T15:35:14Z")
> **I didn't read carefully :confused:**
>
> I’m not quite sure what you wanted to achieve but your map function essentially maps your entry to a function again. So your SparseVector now stores functions!
>
> ```julia
> julia> a = SparseVector([1, 2])
> 2-element SparseVector{Int64, Int64} with 2 stored entries:
> [1] = 1
> [2] = 2
>
> julia> fs = map(x -> (y -> "hello"), a)[1]("asdasdasdas")
> "hello"
>
> julia> fs = map(x -> (y -> "hello"), a)[1](42)
> "hello"
>
> ```
>
> But mapping over SparseVectors in principle works:
>
> ```julia
> julia> map(x -> x^2, a)
> 2-element SparseVector{Int64, Int64} with 2 stored entries:
> [1] = 1
> [2] = 4
>
> ```
---
### Author:  [@schlichtanders](https://discourse.julialang.org/u/schlichtanders)
#### Post date: [July 8, 2021, 3:36pm UTC](https://discourse.julialang.org/t/sparsearray-cannot-store-arbitrary-type-but-only-types-which-support-zero/64283/3 "2021-07-08T15:36:09Z")
it is intended that it stores functions.
I was expecting that SparseVector can deal with ANY Julia type. Is there anywhere a documentation saying that this is intentionally not the case?
---
### Author:  [@roflmaostc](https://discourse.julialang.org/u/roflmaostc)
#### Post date: [July 8, 2021, 3:37pm UTC](https://discourse.julialang.org/t/sparsearray-cannot-store-arbitrary-type-but-only-types-which-support-zero/64283/4 "2021-07-08T15:37:43Z")
You’re right, I should read to the end 😃
---
### Author:  [@kristoffer.carlsson](https://discourse.julialang.org/u/kristoffer.carlsson)
#### Post date: [July 8, 2021, 3:48pm UTC](https://discourse.julialang.org/t/sparsearray-cannot-store-arbitrary-type-but-only-types-which-support-zero/64283/5 "2021-07-08T15:48:02Z")
> [@schlichtanders](#):
>
> I was expecting that SparseVector can deal with ANY Julia type. Is there anywhere a documentation saying that this is intentionally not the case?
See [Sparse Arrays · The Julia Language](https://docs.julialang.org/en/v1/stdlib/SparseArrays/)
> Sparse arrays are arrays that contain enough zeros that storing them in a special data structure leads to savings in space and execution time, compared to dense arrays.
---
### Author:  [@stevengj](https://discourse.julialang.org/u/stevengj)
#### Post date: [July 8, 2021, 4:09pm UTC](https://discourse.julialang.org/t/sparsearray-cannot-store-arbitrary-type-but-only-types-which-support-zero/64283/6 "2021-07-08T16:09:05Z")
> [@schlichtanders](#):
>
> Concretely, I cannot map over a SparseVector of Functions.
Probably you want a dictionary/map container (e.g. the built-in `Dict` in Julia), not a `SparseVector`.
---
### Author:  [@schlichtanders](https://discourse.julialang.org/u/schlichtanders)
#### Post date: [July 8, 2021, 4:10pm UTC](https://discourse.julialang.org/t/sparsearray-cannot-store-arbitrary-type-but-only-types-which-support-zero/64283/7 "2021-07-08T16:10:18Z")
thanks a lot, that explains completely, why it expects zero to exist