Czym jest pandas?

Wprowadzenie do Data Science w Pythonie

Hillary Green-Lerman

Lead Data Scientist, Looker

Co potrafi pandas?

Wczytywanie danych tabelarycznych z różnych źródeł
Wyszukiwanie określonych wierszy lub kolumn
Obliczanie statystyk agregacyjnych
Łączenie danych z wielu źródeł

Dane tabelaryczne w pandas

Dane tabelaryczne

+-------------------------------------------------+
|        suspect        |     location    | price |
+-----------------------+-----------------+-------+
| Fred Frequentist      | Petroleum Plaza | 24.95 |
| Ronald Aylmer Fisher  | Clothing Club   | 20.15 |
+-------------------------------------------------+

DataFrame

                suspect        location  price
0      Fred Frequentist  Perolium Plaza  24.95
1  Ronald Aylmer Fisher   Clothing Club  20.15

Pliki CSV

Wczytywanie pliku CSV

import pandas as pd

df = pd.read_csv('ransom.csv')

Wyświetlanie DataFrame

df = pd.read_csv('filename.csv')

print(df)

                 suspect         location          item  price
0         Kirstine Smith  Petroleum Plaza           gas  24.95
1       Fred Frequentist      Burger Mart         fries   1.95
2           Gertrude Cox      Burger Mart         fries   1.95
3   Ronald Aylmer Fisher    Clothing Club         shirt  14.25
4         Kirstine Smith    Clothing Club         dress  20.15
5       Fred Frequentist   Groceries R Us     cucumbers   2.05
6         Kirstine Smith    Clothing Club         dress  20.15
7           Gertrude Cox  Petroleum Plaza   fizzy drink   1.90
8           Gertrude Cox      Burger Mart         fries   1.95
9   Ronald Aylmer Fisher    Clothing Club         shirt  14.25
10  Ronald Aylmer Fisher  Petroleum Plaza       carwash  13.25
11  Ronald Aylmer Fisher    Clothing Club         shirt  14.25
12        Kirstine Smith  Petroleum Plaza           gas  24.95
13      Fred Frequentist   Groceries R Us          eggs   6.50
14          Gertrude Cox  Petroleum Plaza           gas  24.95
15      Fred Frequentist   Groceries R Us          eggs   6.50
16  Ronald Aylmer Fisher   Groceries R Us          eggs   6.50
17      Fred Frequentist   Groceries R Us        cheese   5.00

Inspekcja DataFrame

df.head()

print(df.head())

                 suspect         location          item  price
0         Kirstine Smith  Petroleum Plaza           gas  24.95
1       Fred Frequentist      Burger Mart         fries   1.95
2           Gertrude Cox      Burger Mart         fries   1.95
3   Ronald Aylmer Fisher    Clothing Club         shirt  14.25
4         Kirstine Smith    Clothing Club         dress  20.15

Inspekcja DataFrame

df.info()

print(df.info())

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 26 entries, 0 to 25
Data columns (total 3 columns):
 #   Column        Non-Null Count  Dtype  
 --  ------        --------------  -----  
 0   letter_index  26 non-null     int64 
 1   letter        26 non-null     object 
 2   frequency     26 non-null     float64 
dtypes: float64(1), int64(1), object(1)
memory usage: 704.0+ bytes

Inspekcja DataFrame

Czas na ćwiczenia!

Wprowadzenie do Data Science w Pythonie