CODEWITHSUNDEEP
pythonbioinformaticsrna-seq
ErikaC
ErikaC

Reputation: 65

save as dataframe python

I am really new in python, so I am doing a consultd and I want that the results be save like dataframe instead of be just print in the terminal. Here is my code:

service = Service("https://www.mousemine.org/mousemine/service")
query = service.new_query("Gene")
query.add_view(
    "primaryIdentifier", "symbol", "organism.name",
    "homologues.homologue.primaryIdentifier", "homologues.homologue.symbol",
    "homologues.homologue.organism.name", "homologues.type",
    "homologues.dataSets.name"
)
query.add_constraint("homologues.type", "NONE OF", ["horizontal gene transfer", "least diverged horizontal gene transfer"], code = "B")
query.add_constraint("Gene", "LOOKUP", "ENSMUSG00000026981,ENSMUSG00000068039,ENSMUSG00000035007,ENSMUSG00000022972,", "M. musculus", code = "A")
query.add_constraint("homologues.homologue.organism.name", "=", "Homo sapiens", code = "C")
query.add_constraint("homologues.dataSets.name", "=", "Mouse/Human Orthologies from MGI", code = "D")

   for row in query.rows():
    print(row["primaryIdentifier"], row["symbol"], row["organism.name"], \
        row["homologues.homologue.primaryIdentifier"], 
        row["homologues.homologue.symbol"], \
        row["homologues.homologue.organism.name"], row["homologues.type"], \
        row["homologues.dataSets.name"])

And this is the result that I get it

MGI:1915251 Cfap298 Mus musculus 56683 CFAP298 Homo sapiens orthologue Mouse/Human Orthologies from MGI MGI:2144506 Rundc1 Mus musculus 146923 RUNDC1 Homo sapiens orthologue Mouse/Human Orthologies from MGI MGI:96547 Il1rn Mus musculus 3557 IL1RN Homo sapiens orthologue Mouse/Human Orthologies from MGI MGI:98535 Tcp1 Mus musculus 6950 TCP1 Homo sapiens orthologue Mouse/Human Orthologies from MGI

And it is perfectly ok, but I need it in a dataframe. And if I can the consult using a table with all the ID and not have to writing one by one (because there are 14000) that will be amazing.

Upvotes: 1

Views: 76

Answers (3)

Corralien
Corralien

Reputation: 120549

Your example is not reproducible because we can't construct the query but I suppose, this should work:

import pandas as pd

df = pd.DataFrame(list(query.rows()))

# OR

df = pd.DataFrame(query.rows(), columns=query.views)

Output:

>>> df
  Gene.briefDescription                                   Gene.description   Gene.id  ...  Gene.homologues.homologue.organism.name Gene.homologues.type     Gene.homologues.dataSets.name
0                  None  FUNCTION: <B>Automated description from the Al...  23666503  ...                             Homo sapiens           orthologue  Mouse/Human Orthologies from MGI
1                  None  FUNCTION: <B>Automated description from the Al...  23341647  ...                             Homo sapiens           orthologue  Mouse/Human Orthologies from MGI
2                  None  FUNCTION: <B>Automated description from the Al...  23862751  ...                             Homo sapiens           orthologue  Mouse/Human Orthologies from MGI
3                  None  FUNCTION: <B>Automated description from the Al...  23677242  ...                             Homo sapiens           orthologue  Mouse/Human Orthologies from MGI

[4 rows x 21 columns]

Upvotes: 1

Mario
Mario

Reputation: 573

Using a loop:

   df = pd.DataFrame({})

   for row in query.rows():
    data = {'primaryIdentifier': row["primaryIdentifier"],
            'symbol': row["symbol"],
            'organism.name': row["organism.name"],
            'homologues.homologue.primaryIdentifier': row["homologues.homologue.primaryIdentifier"],
            'homologues.homologue.symbol': row["homologues.homologue.symbol"],
            'homologues.homologue.organism.name': row["homologues.homologue.organism.name"],
            'homologues.type': row["homologues.type"],
            'homologues.dataSets.name': row["homologues.dataSets.name"]}
    df = df.append(pd.DataFrame(data), ignore_index = True)

Note that you must do an import pandas as pd and make sure that the data are str.

Upvotes: 1

Krzysztof Szewczyk
Krzysztof Szewczyk

Reputation: 9

Pandas would help you.https://pandas.pydata.org. Feel free to ask questions if you stuck with something.

Upvotes: 0

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