Data kategorikal di pandas

Bekerja dengan Data Kategorikal di Python

Kasey Jones

Research Data Scientist

dtypes: object

adult = pd.read_csv("data/adult.csv")
adult.dtypes

Age                 int64
Workclass          object
fnlgwt              int64
Education          object
Education Num       int64
Marital Status     object
Occupation         object
Relationship       object
...

dtypes: categorical

dtype bawaan:

adult["Marital Status"].dtype

dtype('O')

Jadikan kategorikal:

adult["Marital Status"] = adult["Marital Status"].astype("category")

adult["Marital Status"].dtype

CategoricalDtype(categories=[' Divorced', ' Married-AF-spouse',
' Married-civ-spouse', ' Married-spouse-absent', ' Never-married',
' Separated', ' Widowed'], ordered=False)

Membuat Series kategorikal

my_data = ["A", "A", "C", "B", "C", "A"]

my_series1 = pd.Series(my_data, dtype="category")
print(my_series1)

0    A
1    A
2    C
...
dtype: category
Categories (3, object): [A, B, C]

Membuat Series kategorikal

my_data = ["A", "A", "C", "B", "C", "A"]
my_series2 = pd.Categorical(my_data, categories=["C", "B", "A"], ordered=True)
my_series2

[A, A, C, B, C, A]
Categories (3, object): [C < B < A]

Mengapa gunakan kategorikal: memori

Hemat memori:

adult = pd.read_csv("data/adult.csv")
adult["Marital Status"].nbytes

adult["Marital Status"] = adult["Marital Status"].astype("category")
adult["Marital Status"].nbytes

Tentukan dtype saat membaca data

Buat dictionary:

adult_dtypes = {"Marital Status": "category"}

Atur parameter dtype:

adult = pd.read_csv("data/adult.csv", dtype=adult_dtypes)

Cek dtype:
```
adult["Marital Status"].dtype
```

CategoricalDtype(categories=[' Divorced', ' Married-AF-spouse',
                             ..., ' Widowed'], ordered=False)

Latihan kategori pandas

Bekerja dengan Data Kategorikal di Python