Wat is pandas?
Introductie tot Data Science in Python
Hillary Green-Lerman
Lead Data Scientist, Looker
Wat kan pandas voor je doen?
- Tabellen laden uit verschillende bronnen
- Specifieke rijen of kolommen zoeken
- Aggregatiestatistieken berekenen
- Gegevens uit meerdere bronnen combineren
Tabelgegevens met pandas
Tabelgegevens
+-------------------------------------------------+
| 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
CSV-bestanden
Een CSV laden
import pandas as pd
df = pd.read_csv('ransom.csv')
Een DataFrame weergeven
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
Een DataFrame inspecteren
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
Een DataFrame inspecteren
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
Een DataFrame inspecteren
Laten we oefenen!
Introductie tot Data Science in Python
