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i want to convert a report which is in text format into a xlsx document. but the problem is data in text file has some missing column values

typical report data is like this,
A simple approach that i wanted to follow was to use space as a delimeter but the data is not in a well structured manner

read the first line of the file and split each column by checking if there is more than 1 whitespace. In addition to that you count how long each column is.
after that you can simply go through the other rows containing data and extract the information, by checking the length of the column you are at
(and please don't put images of text into stackoverflow, actual text is better)
EDIT:
python implementation:
import pandas as pd
import re
file = "path/to/file.txt"
with open("file", "r") as f:
line = f.readline()
columns = re.split(" +", line)
column_sizes = [re.finditer(column, line).__next__().start() for column in columns]
column_sizes.append(-1)
# ------
f.readline()
rows = []
while True:
line = f.readline()
if len(line) == 0:
break
elif line[-1] != "\n":
line += "\n"
row = []
for i in range(len(column_sizes)-1):
value = line[column_sizes[i]:column_sizes[i+1]]
row.append(value)
rows.append(row)
columns = [column.strip() for column in columns]
df = pd.DataFrame(data=rows, columns=columns)
print(df)
df.to_excel(file.split(".")[0] + ".xlsx")

You are correct that export from text to csv is not a practical start, however it would be good for import. So here is your 100% well structured source text to be saved into plain text.
And here is the import to Excel

you can use google lens to get your data out of this picture then copy and paste to excel file. the easiest way.
or first convert this into pdf then use google lens. go to file scroll to print option in print setting their is an option of MICROSOFT PRINT TO PDF select that and press print it will ask you for location then give it and use it

Read a text File which has numeric columns (like -10.0, -9.9, +9.9 etc.) through Apache Flink

I have requirement where I need to read a file which is generated by another application and file has 201 numeric column name like: -10.0, -9.9, -9.8, -9.7 .......0.....+9.7, +9.8, +9.9, +10.0 so total I have 201 columns in the file. I am reading many files through Flink but file has string type column name and I am creating an model Object with the attributes as columns name available in file as below
DataSet<Person>> csvInput = env.readCsvFile("file:///path/to/my/textfile")
.pojoType(Person.class, "name", "age", "zipcode");
above code will ready file and Person object will be populated with the values available in the File.
I am facing challenge in new requirement where file columns name is numeric and in Java I cannot create a variable with numeric value along with decimal like -10.0 etc.
like private String -10.0 not allowed in java
I am seeking for a solution, could any one please help me out here.

Java example of joining 2 CSV files based on common column

I have 2 CSV file with the following content.
File 1
Id, Name, last name, city
1,peter,green,newyork
2,sam,red,londan
File 2
Id,Movie,Famous move
1,Hulk,punch
2,Ironman,taking the stone.
File after joining file1 and file2
File
Id, Name, last name, city,Movie,Famous move
1,peter,green,newyork,Hulk,punch
2,sam,red,london,Ironman,taking the stone
How I can join this 2 CSV file based on same column in java.
Any help will be appreciated.
Can anyone help how to achieve this in java. In python it is a 5 line code using PANDAS Lib.

Using Lucene, how to index TXT files into different fields?

I am using the NSF data whose format is txt. Now I have indexed these data and can send a query and got several results. But how can I search something in a selected field (eg. title) ? Because all of these NSF data are totally plain txt file. I do not think Lucene can recognize which part of the file is a "title" or something else. Should I firstly transfer the txt files to XML files (with tags telling Lucene which part is "title")? Can Lucene do that? I have no idea how to split the txt files into several fields. Can anyone please give me some suggestions? Thanks a lot!
BTW, every txt file looks like this:
---begin---
Title: Mitochondrial DNA and Historical Demography
Type: Award
Date: August 1, 1991
Number: 9000006
Abstract: asdajsfhsjdfhsjngfdjnguwiehfrwiuefnjdnfsd
----end----

You have to split the text into the several parts. You can use the resulting strings to create a field for each part of the text, i.e. title.
Create your lucene document with the fields like this:
Document doc = new Document();
doc.add(new Field("title", titleString, Field.Store.NO, Field.Index.TOKENIZED));
doc.add(new Field("abstract", abstractString, Field.Store.NO, Field.Index.TOKENIZED));
and so on. After indexing the document you can search in the title like this: title:dna
More complex queries and mixing multiple fields in the query also possible: +title:dna +abstract:"some example text" -number:935353

Apache Pig process CSV with fields wrapped in quotes

How I can process CSV file where some fields are wrapped in quotes?
Line to process for example (field delimiter is ',')
I am column1, I am column2, "yes, I'm am column3"
The example has three columns. But the following example will say that I have four columns:
A = load '/path/to/file' using PigStorage(',');
Please, any suggestions, link to resource..?

Try loading the data, then do a FOREACH GENERATE to regenerate the data into whatever format you need. For the fields where you need to remove the quotes, use a REPLACE($3, '\"').
data = LOAD 'testdata' USING PigStorage(",");
data = FOREACH data GENERATE
(chararray) $0 AS col1:chararray,
(chararray) $1 AS col2:chararray,
(chararray) REPLACE($3, '\"') AS col3:chararray);