Melting back to long in Python

melt is the inverse of a pivot: wide columns become key-value rows.

import pandas as pd

wide = pd.DataFrame({
    "day": ["mon", "tue"],
    "python": [104, 91],
    "rust": [98, 88],
})

long = wide.melt(id_vars="day", var_name="lang", value_name="tpm")
print(long)
print(long.groupby("lang")["tpm"].mean())

How it works

1. id_vars stays put; everything else is unstacked.
2. var_name and value_name name the two new columns.
3. Long data is what plotting and groupby want.

Keywords and builtins used here

• as
• print

The run, in numbers

Lines

11

Characters to type

229

Tokens

95

Three-star pace

110 tpm

At the three-star pace of 110 tokens a minute, this run takes about 52 seconds.

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Step 4 of 4 in Reshaping & joining, step 22 of 26 in pandas.

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