Date: Fri, 29 Mar 2024 16:53:24 +0100 (CET)
Message-ID: <1582236556.2260.1711727604627@nm-docs>
Subject: Exported From Confluence
MIME-Version: 1.0
Content-Type: multipart/related;
boundary="----=_Part_2259_1368037250.1711727604627"
------=_Part_2259_1368037250.1711727604627
Content-Type: text/html; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
Content-Location: file:///C:/exported.html
On this
Introduction
You can import data from Excel (=
span>.xls and .xlsx) or CSV (.csv<=
span style=3D"color: rgb(62,63,64);"> and .txt) format files to your model. You are ab=
le to specify the import mapping options between file columns and element p=
roperties of the model. Additionally, you can save your maps, collect=
them in groups, manage those groups, and use an entire group instead of a =
single map for data import. Before importing data from Excel or CSV fi=
les to model, create new or open an existing project.
You can choose the following import commands:
<=
/span>
All Excel/CSV file import com=
mands from the File menu.
Preparing Excel or CSV file to import
To import data from Excel or CSV files, the files must met the following=
prerequisites:
- Heading is located in the first row.
- When creating relationships, the spreadsheet must contain the source an=
d target columns. The source and target columns contains the names/qualifie=
d names of elements respectively that are the client and supplier =
;of the relationship.
Recommended prerequisites:
- Eliminate merged cells.
- Every column has a unique column name.
- Every row has the same number and name of columns.
- Every cell has the element name or qualified element name.
Imp=
orting data by using a new map
To import data from an Excel or CSV file to model by using a new ma=
p
- Create new or open an existing pr=
oject.
- Make sure:
- the auto usages of Excel Import Plugin are removed. How =
to >>
- the Excel or CSV file met the basic prerequisites. Basic Prerequisites >><=
/span>
- In the top-left corner of the mod=
eling tool, click the File > Import From > Excel/CSV File > Import =
Using New Map. The Excel/CSV Import =
;dialog opens.
Select the file and specify mapping opt=
ions. How to >>
- In the Mapping area, create mapping between the Excel/CSV file data and modeling tool =
;properties. How=
to >>
- (Optional) Click the Save Map button&nb=
sp;to save your map options as the Im=
port Map. How to >>
- Click the Import button.
The data from the Excel or CSV file is imported to the model according to =
the specified options.
Importing data by using an existing map
To import data from Excel or CSV file to model by using an existing map<=
/p>
- Create new or open an exist=
ing project.
- Make sure:
- the auto usages of Excel Import Plugin are removed. How to >>
- the Excel or CSV file met the basic prerequisites. Basic Prerequisites >>=
- In the top-left corner of the mod=
eling tool, click the File > Import From > Excel/CSV File > Im=
port Using Existing Map.
In the Select Import Map dialog, select existing Import Map.
- Click OK. The Excel/CSV Import dialog opens.
- (Optional) Select the file, change mapping options. How to >>
- (Optional) Click the Save Map button to override the s=
elected Import Map or create a new one. How to >>
- Click the Import button.
The data from the Excel or CSV file is imported to the model according to =
the specified options.
Importing data by using an existing map group
To import data from an Excel or CSV file to model by using an existing m=
ap group
- Create new or open an exist=
ing project.
- Make sure:
- the auto usages of Excel Import Plugin are removed. How to >>
- the Excel or CSV file met the basic prerequisites. Basic Prerequisites >>=
- In the top-left corner of the mod=
eling tool, click the File > Import From > Excel/CSV File > Im=
port Using Existing Map Group.
In the Select Map Group dialog, choose the map group.
Click OK.
The data from Excel or CSV files are imported to the model according to Im=
port Maps and their order in the Map Group.
Related pages
------=_Part_2259_1368037250.1711727604627
Content-Type: application/octet-stream
Content-Transfer-Encoding: base64
Content-Location: file:///C:/1725ee83826b66347d4bc2d987bbba16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------=_Part_2259_1368037250.1711727604627--