Join us at FabCon Atlanta from March 16 - 20, 2026, for the ultimate Fabric, Power BI, AI and SQL community-led event. Save $200 with code FABCOMM.
Register now!The Power BI Data Visualization World Championships is back! Get ahead of the game and start preparing now! Learn more
Hello,
One column in my table is a list of strings. I would like to change the strings to lower case if their lenghts is greater than 1.
| Name | Types |
| N1 | A,ABC,B,CDF,DF |
| N2 | H,JKL,BG,DC,C |
Convert to
| Name | Types |
| N1 | A,abc,B,cdf,df |
| N2 | H,jkl,bg,dc,C |
Can somebody help?
Thank you
Solved! Go to Solution.
Here is one way to do this...
= Table.TransformColumns(previousQueryStep, {{"Types", each Text.Combine(List.Transform(Text.Split(_, ","), each if Text.Length(_) > 1 then Text.Lower(_) else _), ","), type text}})
Using your example table you end up with...
Proud to be a Super User! | |
For fun only, to incorporate the power of regex,
import re
import numpy as np
df['Types']=np.vectorize(lambda string:re.compile(r'[a-z]{2,}(?=\b)',flags=re.I).sub(lambda match:str.lower(match.group(0)),string))(df['Types'])let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45W8jNUUFBQ0lFy1HF0ctZx0nF2cdNxcVOK1QFKGQHFPXS8vH10nNx1XJx1nJViYwE=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Name = _t, Types = _t]),
#"Run Python script" = Python.Execute("import re#(lf)import numpy as np#(lf)df['Types']=np.vectorize(lambda string:re.compile(r'[a-z]{2,}(?=\b)',flags=re.I).sub(lambda match:str.lower(match.group(0)),string))(df['Types'])",[df=Source]),
df = #"Run Python script"{[Name="df"]}[Value]
in
df
Expertise = List.Accumulate( {Days as from Today}, {Skills and Knowledge}, (Current, Everyday) => Current & Day.LearnAndPractise(Everyday) ) |
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45W8jNUUFBQ0lFy1HF0ctZx0nF2cdNxcVOK1QFKGQHFPXS8vH10nNx1XJx1nJViYwE=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [#"Name " = _t, Types = _t]),
chars = List.Buffer({"a".."z", "A".."Z"}),
result = Table.TransformColumns(
Source,
{
"Types",
(x) => Text.Combine(
List.Transform(
Text.Split(x, ","),
(w) => if List.Contains(chars, w) then w else Text.Lower(w)
),
","
)
}
)
in
result
Here is one way to do this...
= Table.TransformColumns(previousQueryStep, {{"Types", each Text.Combine(List.Transform(Text.Split(_, ","), each if Text.Length(_) > 1 then Text.Lower(_) else _), ","), type text}})
Using your example table you end up with...
Proud to be a Super User! | |
Check out the November 2025 Power BI update to learn about new features.
Advance your Data & AI career with 50 days of live learning, contests, hands-on challenges, study groups & certifications and more!
| User | Count |
|---|---|
| 10 | |
| 6 | |
| 5 | |
| 5 | |
| 3 |