Was ist pandas?
Einführung in Data Science mit Python
Hillary Green-Lerman
Lead Data Scientist, Looker
Was kann pandas für dich tun?
- Tabellarische Daten aus verschiedenen Quellen laden
- Nach bestimmten Zeilen oder Spalten suchen
- Aggregierte Statistiken berechnen
- Daten aus verschiedenen Quellen zusammenführen
Tabellarische Daten mit pandas
Tabellarische Daten
+-------------------------------------------------+
| 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-Dateien
CSV-Daten laden
import pandas as pd
df = pd.read_csv('ransom.csv')
Anzeigen eines 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
Struktur von DataFrames
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
Struktur von DataFrames
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
Struktur von DataFrames
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Einführung in Data Science mit Python
