Ce este pandas?
Introducere în Data Science cu Python
Hillary Green-Lerman
Lead Data Scientist, Looker
Ce poate face pandas pentru dumneavoastră?
- Încărcarea datelor tabulare din diverse surse
- Căutarea unor rânduri sau coloane specifice
- Calculul statisticilor agregate
- Combinarea datelor din mai multe surse
Date tabulare cu pandas
Date tabulare
+-------------------------------------------------+
| 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
Fișiere CSV
Încărcarea unui fișier CSV
import pandas as pd
df = pd.read_csv('ransom.csv')
Afișarea unui 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
Inspectarea unui 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
Inspectarea unui 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
Inspectarea unui DataFrame
Să exersăm!
Introducere în Data Science cu Python
