visibilityStatic layout preview of Fix Missing Values, shown with a file imported and a completed run (per-column missingness profile + before/after results). All pages →
Fix Missing Values
Find blank cells (even hidden ones) and fill them in or remove them.
Tip: files imported on the Home screen are picked up here automatically.
upload_file Drag and drop file hereUp to 1.5 GB · CSV, TSV, XLSX, XLS
survey_responses.csv684 KB
Preview: survey_responses.csv
2,150 rows, 6 columns
respondent_id
age
region
income
satisfaction
comments
0
R-1001
34
West
52000
4
great service
1
R-1002
N/A
East
3
?
2
R-1003
41
-
61000
NULL
none
3
R-1004
29
South
N/A
5
quick
Options
Missingness profile
Rows
2,150
Cells missing
1,043
% cells missing
8.1%
Complete rows
1,388
column
dtype
missing
missing_pct
disguised
has_missing
respondent_id
object
0
0.0%
0
False
age
float64
187
8.7%
61
True
region
object
142
6.6%
142
True
income
float64
329
15.3%
118
True
satisfaction
float64
95
4.4%
40
True
comments
object
290
13.5%
290
True
Strategy
detect-only (standardize sentinels to NaN, no fill or drop) safe-fill (numeric → median, categorical → mode) drop-incomplete (drop any row with missing)
detect-only: replace 'N/A', '-', 'NULL', etc. with real NaN, then stop. safe-fill: also fill — numeric columns with median, others with mode. drop-incomplete: also drop every row that has any missing cell.
Advanced options
Detection
check Standardize disguised nulls to NaN
N/A, n/a, NA, NULL, null, None, -, --, ?, #N/A
Matched case-insensitively after stripping whitespace.
Strategy override
(use preset)
drop_row / drop_col use the thresholds below. mean / median / interpolate are numeric only — non-numeric columns fall back to the categorical strategy.