krm_ndl #
This file compiles links to the images of the Kanchi-in manuscript of the Ruiju Myōgishō that are publicly available in the National Diet Library Digital Collections.
This data cross-references the locations within the Kanchi-in manuscript of the Ruiju Myōgishō with their corresponding URLs in the National Diet Library Digital Collections. The file name is KRM_ndl.tsv
.
This data indicates the volume name, radical character, Kazama edition page number, Tenri edition page number, and the URL for the National Diet Library Digital Collections.
Next, a sample of the beginning of the data is shown below.
Book | Radical | Kazama | Tenri | NDL_url |
---|---|---|---|---|
仏上 | 人 | 1 | 23 | https://dl.ndl.go.jp/info:ndljp/pid/2586891/6 |
仏上 | 人 | 2 | 24 | https://dl.ndl.go.jp/info:ndljp/pid/2586891/7 |
Integration with krm_main #
To integrate with krm_main, you can ask the following questions using generative AI tools like ChatGPT or Gemini to get appropriate answers. While the instructions here are to use Excel, if you wish to process the data with Python, simply replace Excel with Python.
Below are examples of questions and answers for ChatGPT.
Questions #
How can I join the krm_main.tsv
and krm_ndl.tsv
files in Excel using the kazama_location
column in krm_main.tsv
and the Kazama
column in krm_ndl.tsv
? Please also include the following mapping:
- “仏上” → “K01”
- “仏中” → “K02”
- “仏下本” → “K03”
- “仏下末” → “K04”
- “法上” → “K05”
- “法中” → “K06”
- “法下” → “K07”
- “僧上” → “K08”
- “僧中” → “K09”
- “僧下” → “K10”
Here are the sample data for the files:
Sample krm_main.tsv
:
#
entry_id | hanzi_id | kazama_location | tenri_location | volume_name | radical_name | volume_radical_index | hanzi_entry | original_entry | definition |
---|---|---|---|---|---|---|---|---|---|
F00001 | S00001 | K01001310 | Ta023310 | 仏上 | 人 | v1#1 | 人 | 〇 | 音仁(LV)「ニン」 ヒト(HL) ワレ(LL) サネ マホル ユク |
F00002 | S00002 | K01001331 | Ta023331 | 仏上 | 人 | v1#1 | 一/人 | 〇/〇 | ヒトリ(LH_) |
F00003 | S00004 | K01001341 | Ta023341 | 仏上 | 人 | v1#1 | 二/人 | 〇/〇 | フタリ(HHL) |
Sample krm_ndl.tsv
:
#
Book | Radical | Kazama | Tenri | NDL_url |
---|---|---|---|---|
仏上 | 人 | 1 | 23 | https://dl.ndl.go.jp/info:ndljp/pid/2586891/6 |
仏上 | 人 | 2 | 24 | https://dl.ndl.go.jp/info:ndljp/pid/2586891/7 |
仏上 | 人 | 3 | 25 | https://dl.ndl.go.jp/info:ndljp/pid/2586891/7 |
Answers #
To join the krm_main.tsv
and krm_ndl.tsv
files in Excel using the kazama_location
column in krm_main.tsv
and the Kazama
column in krm_ndl.tsv
, follow these steps:
-
Prepare the Data:
- Import both the
krm_main.tsv
andkrm_ndl.tsv
files into Excel as separate sheets. Name themkrm_main
andkrm_ndl
.
- Import both the
-
Create a Mapping Table:
- Create a new sheet (for example, named “Mapping”) to include the mapping between
kazama_location
andKazama
codes. Use the following mapping:
kazama_location Kazama 仏上 K01 仏中 K02 仏下本 K03 仏下末 K04 法上 K05 法中 K06 法下 K07 僧上 K08 僧中 K09 僧下 K10 - Create a new sheet (for example, named “Mapping”) to include the mapping between
-
Lookup the Kazama Code:
- In the
krm_main
sheet, add a new column (e.g., “Kazama Code”). - Use the
VLOOKUP
function to lookup the value inkazama_location
and return the correspondingKazama
code from the “Mapping” sheet.
Enter the following formula in the new column (e.g., G2):
=VLOOKUP(D2, Mapping!$A$2:$B$11, 2, FALSE)
D2
is the cell in thekazama_location
column in thekrm_main
sheet.Mapping!$A$2:$B$11
refers to the range in the “Mapping” sheet that contains thekazama_location
andKazama
values.
- In the
-
Join the Data:
- Use
VLOOKUP
again to joinkrm_main
andkrm_ndl
based on theKazama
code. - For example, in the
krm_main
sheet, use this formula to retrieve theNDL_url
from thekrm_ndl
sheet:
=VLOOKUP(G2, krm_ndl!$C$2:$E$100, 3, FALSE)
G2
is the “Kazama Code” column in thekrm_main
sheet.krm_ndl!$C$2:$E$100
refers to the range in thekrm_ndl
sheet that includes theKazama
andNDL_url
columns.
- Use
Summary #
With this approach, you can:
- Create a mapping table between
kazama_location
andKazama
codes. - Use
VLOOKUP
to joinkrm_main
andkrm_ndl
based on theKazama
code.
This method allows you to efficiently join the data using the mapping and Excel functions.