Transposing
Transposing swaps rows and columns, like rotating the table a quarter turn.
In this page:
Syntax
transposed = df.TTransposing
df.T flips rows and columns, so the index becomes the column headers. It is useful for viewing wide summaries such as describe() output. Mixed dtypes become object after transposing.
Note:
df.describe().T is often easier to read.
Example: Transposing
import pandas as pd
df = pd.DataFrame({"a": [1, 2], "b": [3, 4]}, index=["r1", "r2"])
print(df.T)
print(df.describe().T[["mean", "max"]])
# Output:
# r1 r2
# a 1 2
# b 3 4
# mean max
# a 1.5 2.0
# b 3.5 4.0Related Topics
{# common_mistakes/chapter_summary/browser_support: on Hindi pages the
view already swaps in the hi_ translation fields (or blanks these
out if untranslated), so this renders correctly for both languages
without a lang_code check here. #}
Common Mistakes
- Losing dtypes after transposing mixed data
- Forgetting the index becomes columns
- Transposing very large tables
Chapter Summary
- .T swaps rows and columns
- Index becomes column headers
- Mixed dtypes become object
- describe().T is a handy view
🔒
Chapter Quiz — Complete all 6 topics to unlock
0/6 topics done
Complete these topics first: