# Converting Pandas DataFrame to Julia DataFrame?

**URL:** <https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356>\
**Category:** General Usage\
**Created:** [September 22, 2018, 9:02pm UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356 "2018-09-22T21:02:18Z")\
**Posts on this page:** 20\
**Page:** 1

<div class="post-metadata">

**Author:** ![tk3369](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/tk3369/32/2824_2.png) [@tk3369](https://discourse.julialang.org/u/tk3369)\
**Post date:** [September 22, 2018, 9:02pm UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356/1 "2018-09-22T21:02:18Z")

</div>

[Pandas.jl](https://github.com/JuliaPy/Pandas.jl) is pretty nice. Is there an easy way to convert from Pandas DataFrame to Julia DataFrame?

e.g.

```julia
julia> df = read_csv("iris.csv")
     Unnamed: 0 Sepal.Length Sepal.Width Petal.Length Petal.Width Species
0 1 5.1 3.5 1.4 0.2 setosa
1 2 4.9 3.0 1.4 0.2 setosa
2 3 4.7 3.2 1.3 0.2 setosa
3 4 4.6 3.1 1.5 0.2 setosa
4 5 5.0 3.6 1.4 0.2 setosa
5 6 5.4 3.9 1.7 0.4 setosa
6 7 4.6 3.4 1.4 0.3 setosa
7 8 5.0 3.4 1.5 0.2 setosa
8 9 4.4 2.9 1.4 0.2 setosa
9 10 4.9 3.1 1.5 0.1 setosa
10 11 5.4 3.7 1.5 0.2 setosa
...

julia> typeof(df)
Pandas.DataFrame

```

---

<div class="post-metadata">

**Author:** ![dpsanders](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/dpsanders/32/3573_2.png) [@dpsanders](https://discourse.julialang.org/u/dpsanders)\
**Post date:** [September 22, 2018, 9:24pm UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356/2 "2018-09-22T21:24:08Z")

</div>

As far as I understand, the standard conversion tool is

> **[GitHub - queryverse/IterableTables.jl: Implementations of the TableTraits.jl...](https://github.com/queryverse/IterableTables.jl)**
>
> Implementations of the TableTraits.jl interface for various packages - GitHub - queryverse/IterableTables.jl: Implementations of the TableTraits.jl interface for various packages

Provided that there is an interface from pandas.jl. If not, one should be built.

---

<div class="post-metadata">

**Author:** ![davidanthoff](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/davidanthoff/32/223493_2.png) [@davidanthoff](https://discourse.julialang.org/u/davidanthoff)\
**Post date:** [September 23, 2018, 4:07am UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356/3 "2018-09-23T04:07:14Z")

</div>

Pandas.jl has support for this, so it should just work.

---

<div class="post-metadata">

**Author:** ![tk3369](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/tk3369/32/2824_2.png) [@tk3369](https://discourse.julialang.org/u/tk3369)\
**Post date:** [September 23, 2018, 6:04am UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356/4 "2018-09-23T06:04:27Z")

</div>

Not for me…

```julia
julia> DataFrames.DataFrame(df)
ERROR: MethodError: no method matching DataFrames.DataFrame(::Pandas.DataFrame)
Closest candidates are:
  DataFrames.DataFrame(::Any, ::DataStreams.Data.Schema, ::Type{S}, ::Bool; reference) where S at /Users/tomkwong/.julia/packages/DataFrames/utxEh/src/abstractdataframe/io.jl:295
  DataFrames.DataFrame(::Array{Any,1}, ::DataFrames.Index) at /Users/tomkwong/.julia/packages/DataFrames/utxEh/src/dataframe/dataframe.jl:87
  DataFrames.DataFrame(; kwargs...) at /Users/tomkwong/.julia/packages/DataFrames/utxEh/src/dataframe/dataframe.jl:142

```

So I tried to convert a `TypedTable` to `DataFrame` as noted in `IterableTables`’s README file and it’s giving weird results. Perhaps things got broken in the transition to 1.0?

```julia
julia> t = TypedTables.Table(a = [1, 2, 3], b = [2.0, 4.0, 6.0])
Table with 2 columns and 3 rows:
     a b
   ┌───────
 1 │ 1 2.0
 2 │ 2 4.0
 3 │ 3 6.0

julia> DataFrames.DataFrame(t)
┌ Warning: passing columns argument with non-AbstractVector entries is deprecated
│ caller = top-level scope at none:0
└ @ Core none:0
1×3 DataFrames.DataFrame
│ Row │ x1 │ x2 │ x3 │
├─────┼──────────────────┼──────────────────┼──────────────────┤
│ 1 │ (a = 1, b = 2.0) │ (a = 2, b = 4.0) │ (a = 3, b = 6.0) │

```

---

<div class="post-metadata">

**Author:** ![Ajaychat3](https://avatars.discourse-cdn.com/v4/letter/a/ecd19e/32.png) [@Ajaychat3](https://discourse.julialang.org/u/Ajaychat3)\
**Post date:** [September 23, 2018, 10:09am UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356/5 "2018-09-23T10:09:17Z")

</div>

I did this and it works. I am using Julia 1.0 on win 10

```julia
using Pandas

df=read_csv("iris.csv");
typeof(df)

Pandas.DataFrame

df1=DataFrames.DataFrame(df);
typeof(df1)

DataFrame
```

---

<div class="post-metadata">

**Author:** ![tk3369](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/tk3369/32/2824_2.png) [@tk3369](https://discourse.julialang.org/u/tk3369)\
**Post date:** [September 23, 2018, 5:19pm UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356/6 "2018-09-23T17:19:17Z")

</div>

I replicated the same problem with a new project environment. I’m using Mac but I doubt the OS plays a role in this issue. Do you have the same package versions as mine?

```julia
(v1.0) pkg> activate .

(PandasTest) pkg> add Pandas DataFrames
  Updating registry at `~/.julia/registries/General`
  Updating git-repo `https://github.com/JuliaRegistries/General.git`
 Resolving package versions...
  Updating `Project.toml`
  [a93c6f00] + DataFrames v0.13.1
  [eadc2687] + Pandas v1.0.1
  Updating `Manifest.toml`
  [b99e7846] + BinaryProvider v0.5.0
  [324d7699] + CategoricalArrays v0.3.13
  [944b1d66] + CodecZlib v0.5.0
  [34da2185] + Compat v1.1.0
  [8f4d0f93] + Conda v1.0.1
  [a93c6f00] + DataFrames v0.13.1
  [9a8bc11e] + DataStreams v0.4.1
  [864edb3b] + DataStructures v0.13.0
  [e7dc6d0d] + DataValues v0.4.5
  [82899510] + IteratorInterfaceExtensions v0.1.1
  [682c06a0] + JSON v0.19.0
  [50d2b5c4] + Lazy v0.13.1
  [1914dd2f] + MacroTools v0.4.4
  [e1d29d7a] + Missings v0.3.1
  [bac558e1] + OrderedCollections v1.0.1
  [eadc2687] + Pandas v1.0.1
  [438e738f] + PyCall v1.18.4
  [189a3867] + Reexport v0.2.0
  [a2af1166] + SortingAlgorithms v0.3.1
  [2913bbd2] + StatsBase v0.25.0
  [3783bdb8] + TableTraits v0.3.1
  [382cd787] + TableTraitsUtils v0.3.1
  [3bb67fe8] + TranscodingStreams v0.8.1
  [81def892] + VersionParsing v1.1.2
  [ea10d353] + WeakRefStrings v0.5.3
  [2a0f44e3] + Base64 
  [ade2ca70] + Dates 
  [8bb1440f] + DelimitedFiles 
  [8ba89e20] + Distributed 
  [9fa8497b] + Future 
  [b77e0a4c] + InteractiveUtils 
  [76f85450] + LibGit2 
  [8f399da3] + Libdl 
  [37e2e46d] + LinearAlgebra 
  [56ddb016] + Logging 
  [d6f4376e] + Markdown 
  [a63ad114] + Mmap 
  [44cfe95a] + Pkg 
  [de0858da] + Printf 
  [3fa0cd96] + REPL 
  [9a3f8284] + Random 
  [ea8e919c] + SHA 
  [9e88b42a] + Serialization 
  [1a1011a3] + SharedArrays 
  [6462fe0b] + Sockets 
  [2f01184e] + SparseArrays 
  [10745b16] + Statistics 
  [8dfed614] + Test 
  [cf7118a7] + UUIDs 
  [4ec0a83e] + Unicode 

julia> using Pandas: read_csv

julia> using DataFrames: DataFrame

julia> df1 = read_csv("iris.csv"); 

julia> df2 = DataFrame(df1)
ERROR: MethodError: no method matching DataFrame(::Pandas.DataFrame)
Closest candidates are:
  DataFrame(::Any, ::DataStreams.Data.Schema, ::Type{S}, ::Bool; reference) where S at /Users/tomkwong/.julia/packages/DataFrames/utxEh/src/abstractdataframe/io.jl:295
  DataFrame(::Array{Any,1}, ::DataFrames.Index) at /Users/tomkwong/.julia/packages/DataFrames/utxEh/src/dataframe/dataframe.jl:87
  DataFrame(; kwargs...) at /Users/tomkwong/.julia/packages/DataFrames/utxEh/src/dataframe/dataframe.jl:142

julia> versioninfo()
Julia Version 1.0.0
Commit 5d4eaca0c9 (2018-08-08 20:58 UTC)
Platform Info:
  OS: macOS (x86_64-apple-darwin14.5.0)
  CPU: Intel(R) Core(TM) i5-4258U CPU @ 2.40GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-6.0.0 (ORCJIT, haswell)
Environment:
  JULIA_NUM_THREADS = 4

```

---

<div class="post-metadata">

**Author:** ![kristoffer.carlsson](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/kristoffer.carlsson/32/22_2.png) [@kristoffer.carlsson](https://discourse.julialang.org/u/kristoffer.carlsson)\
**Post date:** [September 23, 2018, 5:30pm UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356/7 "2018-09-23T17:30:23Z")

</div>

Try with DataFrames master

---

<div class="post-metadata">

**Author:** ![Ajaychat3](https://avatars.discourse-cdn.com/v4/letter/a/ecd19e/32.png) [@Ajaychat3](https://discourse.julialang.org/u/Ajaychat3)\
**Post date:** [September 24, 2018, 5:24am UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356/8 "2018-09-24T05:24:15Z")

</div>

@tk3369

I don’t know what is happending. Today I run the same command and it throws an error

```julia
using Pandas

df=read_csv("iris.csv");
@show typeof(df)

Pandas.DataFrame

using DataFrames,Data
df1=DataFrames.DataFrame(df);
typeof(df1)

MethodError: no method matching DataFrames.DataFrame(::Pandas.DataFrame)
Closest candidates are:
  DataFrames.DataFrame(::Any, !Matched::DataStreams.Data.Schema, !Matched::Type{S}, !Matched::Bool; reference) where S at C:\Users\chatura\.julia\packages\DataFrames\utxEh\src\abstractdataframe\io.jl:295
  DataFrames.DataFrame(!Matched::Array{Any,1}, !Matched::DataFrames.Index) at C:\Users\chatura\.julia\packages\DataFrames\utxEh\src\dataframe\dataframe.jl:87
  DataFrames.DataFrame(; kwargs...) at C:\Users\chatura\.julia\packages\DataFrames\utxEh\src\dataframe\dataframe.jl:142
  ...

Stacktrace:
 [1] top-level scope at In[4]:2

```

---

<div class="post-metadata">

**Author:** ![tk3369](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/tk3369/32/2824_2.png) [@tk3369](https://discourse.julialang.org/u/tk3369)\
**Post date:** [September 24, 2018, 5:29am UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356/9 "2018-09-24T05:29:55Z")

</div>

It looks like that you’re not using `master`… same problem as mine before.

See if you have this:

```julia
(v1.0) pkg> st
  [a93c6f00] DataFrames v0.13.1+ #master (https://github.com/JuliaData/DataFrames.jl.git)

```

If not, just switch over:

```julia
] add DataFrames#master

```

---

<div class="post-metadata">

**Author:** ![Ajaychat3](https://avatars.discourse-cdn.com/v4/letter/a/ecd19e/32.png) [@Ajaychat3](https://discourse.julialang.org/u/Ajaychat3)\
**Post date:** [September 24, 2018, 5:37am UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356/10 "2018-09-24T05:37:41Z")

</div>

Yes it works after using master.

---

<div class="post-metadata">

**Author:** ![davidanthoff](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/davidanthoff/32/223493_2.png) [@davidanthoff](https://discourse.julialang.org/u/davidanthoff)\
**Post date:** [September 29, 2018, 5:26am UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356/11 "2018-09-29T05:26:45Z")

</div>

So the conversion between [Pandas.jl](https://github.com/JuliaPy/Pandas.jl) and [DataFrames.jl](https://github.com/JuliaData/DataFrames.jl) should just work on julia 1.0:

```julia
(foo) pkg> st
    Status `C:\Users\david\.julia\environments\foo\Project.toml`
  [a93c6f00] DataFrames v0.14.0
  [eadc2687] Pandas v1.0.2

julia> using DataFrames, Pandas

julia> df = DataFrames.DataFrame(a=rand(10), b=rand(10))
10×2 DataFrames.DataFrame
│ Row │ a │ b │
│ │ Float64 │ Float64 │
├─────┼───────────┼───────────┤
│ 1 │ 0.098737 │ 0.912536 │
│ 2 │ 0.66538 │ 0.770032 │
│ 3 │ 0.767376 │ 0.635237 │
│ 4 │ 0.353171 │ 0.169174 │
│ 5 │ 0.330284 │ 0.453514 │
│ 6 │ 0.363861 │ 0.64091 │
│ 7 │ 0.622878 │ 0.672581 │
│ 8 │ 0.0130092 │ 0.0542869 │
│ 9 │ 0.779855 │ 0.0753927 │
│ 10 │ 0.943342 │ 0.395862 │

julia> pd = Pandas.DataFrame(df)
          a b
0 0.098737 0.912536
1 0.665380 0.770032
2 0.767376 0.635237
3 0.353171 0.169174
4 0.330284 0.453514
5 0.363861 0.640910
6 0.622878 0.672581
7 0.013009 0.054287
8 0.779855 0.075393
9 0.943342 0.395862

julia> DataFrames.DataFrame(pd)
10×2 DataFrames.DataFrame
│ Row │ a │ b │
│ │ Float64 │ Float64 │
├─────┼───────────┼───────────┤
│ 1 │ 0.098737 │ 0.912536 │
│ 2 │ 0.66538 │ 0.770032 │
│ 3 │ 0.767376 │ 0.635237 │
│ 4 │ 0.353171 │ 0.169174 │
│ 5 │ 0.330284 │ 0.453514 │
│ 6 │ 0.363861 │ 0.64091 │
│ 7 │ 0.622878 │ 0.672581 │
│ 8 │ 0.0130092 │ 0.0542869 │
│ 9 │ 0.779855 │ 0.0753927 │
│ 10 │ 0.943342 │ 0.395862 │

julia>

```

The [TableTraits.jl](https://github.com/queryverse/TableTraits.jl)/[IterableTables.jl](https://github.com/queryverse/IterableTables.jl) integration for [TypedTables.jl](https://github.com/FugroRoames/TypedTables.jl) does not yet work on julia 1.0.

---

<div class="post-metadata">

**Author:** ![brilhana](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/brilhana/32/2112_2.png) [@brilhana](https://discourse.julialang.org/u/brilhana)\
**Post date:** [October 12, 2018, 11:10pm UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356/12 "2018-10-12T23:10:48Z")

</div>

I’m on `DataFrames#master` and I’m getting this error:

`ERROR: PyError ($(Expr(:escape, :(ccall(#= /Users/brilhana/.julia/packages/PyCall/0jMpb/src/pyfncall.jl:44 =# @pysym(:PyObject_Call), PyPtr, (PyPtr, PyPtr, PyPtr), o, pyargsptr, kw))))) <class 'KeyError'> KeyError('0')`

Creating a `Pandas.DataFrame` works fine but conversion to a `DataFrames.DataFrame` fails.

---

<div class="post-metadata">

**Author:** ![davidanthoff](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/davidanthoff/32/223493_2.png) [@davidanthoff](https://discourse.julialang.org/u/davidanthoff)\
**Post date:** [October 12, 2018, 11:41pm UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356/13 "2018-10-12T23:41:47Z")

</div>

Any chance you could provide a small code example that constructs a minimal `Pandas.DataFrame` that then can’t be converted to a `DataFrames.DataFrame`?

---

<div class="post-metadata">

**Author:** ![brilhana](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/brilhana/32/2112_2.png) [@brilhana](https://discourse.julialang.org/u/brilhana)\
**Post date:** [October 12, 2018, 11:50pm UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356/14 "2018-10-12T23:50:28Z")

</div>

```julia
using DataFrames, HTTP, Pandas

const URL = "https://api.bitfinex.com/v1"

function symbols()
    r = HTTP.get("$URL/symbols")
    s = String(r.body)
    return Pandas.read_json(s) # Creates a Pandas.DataFrame.
end

df = symbols()

df2 = DataFrames.DataFrame(df) # This will fail.

```

---

<div class="post-metadata">

**Author:** ![davidanthoff](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/davidanthoff/32/223493_2.png) [@davidanthoff](https://discourse.julialang.org/u/davidanthoff)\
**Post date:** [November 12, 2018, 7:56pm UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356/15 "2018-11-12T19:56:23Z")

</div>

I [tracked](https://github.com/JuliaPy/Pandas.jl/issues/40) this down to a weird indexing situation in [Pandas.jl](https://github.com/JuliaPy/Pandas.jl). For now, it might be enough to rename the column, but I’m not sure.

---

<div class="post-metadata">

**Author:** ![Ajaychat3](https://avatars.discourse-cdn.com/v4/letter/a/ecd19e/32.png) [@Ajaychat3](https://discourse.julialang.org/u/Ajaychat3)\
**Post date:** [November 13, 2018, 4:02am UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356/16 "2018-11-13T04:02:37Z")

</div>

I am highlighting a separate connected issue. I am using Julia to read HDF file created in Python. Then I convert it to a Pandas DataFrame which seems to work fine. Subsequently I try to convert this to DataFrames.DataFrame (which I cannot do directly from Python), and the output I get is all messed up.

I am using Julia 1.0 and list of package version is given below.

```julia
using PyCall: @pyimport
@pyimport pandas as pd

#import os
file=joinpath(pwd(),"Data") 
# dpli_data = pd.read_csv( os.path.join(os.getcwd(), "dpli_data_Final.csv"),low_memory=False)
data_store = pd.HDFStore(joinpath(file,"Dpli_data_warehouse.h5"))

# ########Retrieve data using key
dpli_data = data_store["data_0818"];

# # data_store.close()
@show typeof(dpli_data)
typeof(dpli_data) = PyCall.PyObject

dpli_data
   Age	Sex	YOR	SA	Plan	Mode	LOB	PTD	AGT	EXPR	Type	EMR	PT	PPT	SubStatus	DOBLA	UW	TPCL	PML	TPML	APE	DOI	CHNL	LA_OCC	LA_INC	LA_CITY	LA_ID	PO_ID	NOMINEE	AG_CITY	AGT_BR	REDF_CITY	DTH_CLM	POLINV	ADVFIND	EXAPP	DEF_ND	LA_AG_CITY	LA_BR_CITY	MOR	MOI	DUR	DURIF	AGT_BLK
PolNo																																												
1	40	0	2008	250000.0	31	0	3	20180903	70001019	0.00	1	0	30	30	13	19680803	1	0	0	0	50000.0000	20080903	1	7	500000.0	1399	21	21	4	1980	2123	0	0	0	0	0	0	0	0	9	9	120	119	0
2	40	0	2008	250000.0	31	0	3	20180903	70001019	0.00	1	0	30	30	13	19680803	1	0	0	0	50000.0000	20080903	1	7	500000.0	1399	21	21	32	1980	2123	0	0	0	0	0	0	0	0	9	9	120	119	0
3	32	1	2008	50000.0	31	3	3	20180905	70001019	0.00	1	0	30	30	13	19760822	1	0	0	0	10000.0000	20080905	1	6	2000000.0	1980	21	21	39	1980	2123	0	0	0	0	0	0	1	0	9	9	120	119	0
4	38	0	2008	250000.0	31	0	3	20140908	70001019	0.00	1	0	14	14	8	19700804	1	0	0	0	50000.0000	20080908	1	6	2400000.0	1980	21	21	32	1980	2123	0	0	0	0	0	0	1	0	9	9	72	72	0
5	48	0	2008	50000.0	31	0	3	20110911	70001019	0.00	1	0	5	5	9	19600108	1	0	0	0	10000.0000	20080911	1	2	0.0	1399	27	27	20	1980	2123	0	0	0	0	0	0	0	0	9	9	36	36	0

using Pandas
dpli_data1=Pandas.DataFrame(dpli_data)
Pandas.head(dpli_data1)

        Age Sex YOR SA Plan ... MOR MOI DUR DURIF AGT_BLK
PolNo ...                                  
1 40 0 2008 250000.0 31 ... 9 9 120 119 0
2 40 0 2008 250000.0 31 ... 9 9 120 119 0
3 32 1 2008 50000.0 31 ... 9 9 120 119 0
4 38 0 2008 250000.0 31 ... 9 9 72 72 0
5 48 0 2008 50000.0 31 ... 9 9 36 36 0

[5 rows x 44 columns]

using DataFrames
dpli_data2=DataFrames.DataFrame(dpli_data1);
typeof(dpli_data2)
DataFrames.DataFrame

DataFrames.head(dpli_data2)

	Age	Sex	YOR	SA	Plan	Mode	LOB	PTD	AGT	EXPR	Type	EMR	PT	PPT	SubStatus	DOBLA	UW	TPCL	PML	TPML	APE	DOI	CHNL	LA_OCC	LA_INC	LA_CITY	LA_ID	PO_ID	NOMINEE	AG_CITY	AGT_BR	REDF_CITY	DTH_CLM	POLINV	ADVFIND	EXAPP	DEF_ND	LA_AG_CITY	LA_BR_CITY	MOR	MOI	DUR	DURIF	AGT_BLK
1	40	0	2008	250000.0	31	0	3	20180903	70001019	0.0	1	0	30	30	13	19680803	1	0	0	0	50000.0	20080903	1	7	500000.0	1399	21	21	4	1980	2123	0	0	0	0	0	0	0	0	9	9	120	119	0
2	0	31	70001019	0.0	0	3	20180903	1	9	50000.0	0	30	30	13	19680803	1	0	0	0	20080903	500000.0	1	7	1399	250000.0	21	21	4	1980	2123	0	0	0	0	0	0	0	0	40	9	120	119	0	2008
3	31	0	9	50000.0	3	20180903	1	0	9	500000.0	30	30	13	19680803	1	0	0	0	20080903	1	250000.0	7	1399	21	0.0	21	4	1980	2123	0	0	0	0	0	0	0	0	40	0	120	119	0	2008	70001019
4	0	3	9	500000.0	20180903	1	0	30	120	250000.0	30	13	19680803	1	0	0	0	20080903	1	7	0.0	1399	21	21	50000.0	4	1980	2123	0	0	0	0	0	0	0	0	40	0	31	119	0	2008	70001019	9
5	3	20180903	120	250000.0	1	0	30	30	119	0.0	13	19680803	1	0	0	0	20080903	1	7	1399	50000.0	21	21	4	500000.0	1980	2123	0	0	0	0	0	0	0	0	40	0	31	0	0	2008	70001019	9	9
6	20180903	1	119	0.0	0	30	30	13	0	50000.0	19680803	1	0	0	0	20080903	1	7	1399	21	500000.0	21	4	1980	50000.0	2123	0	0	0	0	0	0	0	0	40	0	31	0	3	2008	70001019	9	9	120

(v1.0) pkg> st
    Status `C:\Users\chatura\.julia\environments\v1.0\Project.toml`
  [28f2ccd6] ApproxFun v0.10.1
  [c52e3926] Atom v0.7.6
  [6e4b80f9] BenchmarkTools v0.4.1
  [a74b3585] Blosc v0.5.1
  [336ed68f] CSV v0.4.2
  [5d742f6a] CSVFiles v0.10.0
  [aaaa29a8] Clustering v0.12.1
  [944b1d66] CodecZlib v0.5.1
  [f3117721] CombineML v1.1.1
  [8f4d0f93] Conda v1.1.1
  [a93c6f00] DataFrames v0.14.1
  [1313f7d8] DataFramesMeta v0.4.0
  [7806a523] DecisionTree v0.8.1
  [31c24e10] Distributions v0.16.4
  [587475ba] Flux v0.6.8
  [da1fdf0e] FreqTables v0.3.0
  [38e38edf] GLM v1.0.1
  [c91e804a] Gadfly v1.0.0
  [bc5e4493] GitHub v5.0.2
  [cd3eb016] HTTP v0.7.1
  [7073ff75] IJulia v1.14.0
  [033835bb] JLD2 v0.1.2
  [682c06a0] JSON v0.19.0
  [4076af6c] JuMP v0.18.4
  [e5e0dc1b] Juno v0.5.3
  [f0e99cf1] MLBase v0.8.0
  [9920b226] MLDataPattern v0.5.0
  [cc2ba9b6] MLDataUtils v0.4.0
  [1914dd2f] MacroTools v0.4.4
  [6f286f6a] MultivariateStats v0.6.0
  [b8a86587] NearestNeighbors v0.4.2
  [429524aa] Optim v0.17.2
  [eadc2687] Pandas v1.0.2
  [91a5bcdd] Plots v0.21.0
  [92933f4c] ProgressMeter v0.6.1
  [438e738f] PyCall v1.18.5
  [1a8c2f83] Query v0.10.1
  [295af30f] Revise v0.7.12
  [fdea26ae] SIMD v2.0.1
  [3e6341c9] SLEEF v0.5.1
  [3646fa90] ScikitLearn v0.5.0
  [6e75b9c4] ScikitLearnBase v0.4.1
  [60ddc479] StatPlots v0.8.1
  [2913bbd2] StatsBase v0.25.0
  [37b6cedf] Traceur v0.2.0
  [c17dfb99] WinRPM v0.4.2
  [009559a3] XGBoost v0.2.0+ #master (https://github.com/dmlc/XGBoost.jl.git)
  [37e2e46d] LinearAlgebra
  [3fa0cd96] REPL
  [9a3f8284] Random
  [10745b16] Statistics

```

---

<div class="post-metadata">

**Author:** ![Palli](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/palli/32/3380_2.png) [@Palli](https://discourse.julialang.org/u/Palli)\
**Post date:** [June 15, 2020, 11:53am UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356/17 "2020-06-15T11:53:24Z")

</div>

> [@dpsanders](#):
>
> Provided that there is an interface from pandas.jl. If not, one should be built.

The discussion here is from Pandas, meaning Pandas.jl, to DataFrame. I actually have a Python pandas dataframe, and suppose support for it needs to be added to [IterableTables.jl](https://github.com/queryverse/IterableTables.jl) for it too? Or should such conversion be in Pandas.jl or is already? I guess long term, I should get rid of all Python code (I’m porting, in phases).

```julia
julia> using IterableTables

julia> p_df = DataFrame(py"df_SA")
ERROR: ArgumentError: 'PyObject' iterates 'String' values, which doesn't satisfy the Tables.jl `AbstractRow` interface
Stacktrace:
 [1] invalidtable(::PyObject, ::String) at /home/pharaldsson_sym/.julia/packages/Tables/okt7x/src/tofromdatavalues.jl:42
 [2] iterate at /home/pharaldsson_sym/.julia/packages/Tables/okt7x/src/tofromdatavalues.jl:48 [inlined]
 [3] buildcolumns at /home/pharaldsson_sym/.julia/packages/Tables/okt7x/src/fallbacks.jl:185 [inlined]
 [4] columns at /home/pharaldsson_sym/.julia/packages/Tables/okt7x/src/fallbacks.jl:237 [inlined]
 [5] DataFrame(::PyObject; copycols::Bool) at /home/pharaldsson_sym/.julia/packages/DataFrames/S3ZFo/src/other/tables.jl:40
 [6] DataFrame(::PyObject) at /home/pharaldsson_sym/.julia/packages/DataFrames/S3ZFo/src/other/tables.jl:31
 [7] top-level scope at /home/pharaldsson_sym/.julia/packages/PyCall/zqDXB/src/pyeval.jl:232

```

---

<div class="post-metadata">

**Author:** ![gvarthi](https://avatars.discourse-cdn.com/v4/letter/g/e9bcb4/32.png) [@gvarthi](https://discourse.julialang.org/u/gvarthi)\
**Post date:** [June 19, 2020, 1:56pm UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356/18 "2020-06-19T13:56:54Z")

</div>

I also have similar requirement. And, I wonder there is no supported function to read parquet file in Pandas.jl such as read\_parquet(). Hence, I was reading the parquet file from python pandas library and couldn’t able to convert to Julia DataFrame.  
Any suggestions/updatates?

---

<div class="post-metadata">

**Author:** ![jesseventura](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/jesseventura/32/7638_2.png) [@jesseventura](https://discourse.julialang.org/u/jesseventura)\
**Post date:** [August 27, 2020, 5:17am UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356/19 "2020-08-27T05:17:38Z")

</div>

PandasLite.jl implemented read\_parquet ,  
and here, [Julia data storage - #2 by lungben](https://discourse.julialang.org/t/julia-data-storage/44283/2)

---

<div class="post-metadata">

**Author:** ![rashid](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/rashid/32/9398_2.png) [@rashid](https://discourse.julialang.org/u/rashid)\
**Post date:** [July 8, 2021, 1:21pm UTC](https://discourse.julialang.org/t/converting-pandas-dataframe-to-julia-dataframe/15356/20 "2021-07-08T13:21:31Z")

</div>

For anyone coming here from google to convert Pandas dataframes to DataFrames.DataFrame, [this post](https://discourse.julialang.org/t/converting-pandas-dataframe-returned-from-pycall-to-julia-dataframe/43001/2) from another thread contains a function which can do this.