In [3]:
# This Python 3 environment comes with many helpful analytics libraries installed
# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python
# For example, here's several helpful packages to load

import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

# Input data files are available in the read-only "../input/" directory
# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory

import os
for dirname, _, filenames in os.walk('/kaggle/input'):
    for filename in filenames:
        print(os.path.join(dirname, filename))

# You can write up to 5GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using "Save & Run All" 
# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session

/kaggle/input/springleaf-marketing-response/test.csv.zip
/kaggle/input/springleaf-marketing-response/train.csv.zip
/kaggle/input/springleaf-marketing-response/sample_submission.csv.zip
In [9]:
import pandas as pd

PATH = "../input/springleaf-marketing-response/"
train = pd.read_csv(PATH + "train.csv.zip", nrows=200)
train
Out[9]:
ID VAR_0001 VAR_0002 VAR_0003 VAR_0004 VAR_0005 VAR_0006 VAR_0007 VAR_0008 VAR_0009 ... VAR_1926 VAR_1927 VAR_1928 VAR_1929 VAR_1930 VAR_1931 VAR_1932 VAR_1933 VAR_1934 target
0 2 H 224 0 4300 C 0 0 False False ... 98 98 998 999999998 998 998 9998 9998 IAPS 0
1 4 H 7 53 4448 B 1 0 False False ... 98 98 998 999999998 998 998 9998 9998 IAPS 0
2 5 H 116 3 3464 C 0 0 False False ... 98 98 998 999999998 998 998 9998 9998 IAPS 0
3 7 H 240 300 3200 C 0 0 False False ... 98 98 998 999999998 998 998 9998 9998 RCC 0
4 8 R 72 261 2000 N 0 0 False False ... 98 98 998 999999998 998 998 9998 9998 BRANCH 1
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
195 381 R 125 137 2125 N 3 2 False False ... 0 97 997 999999997 400 997 9996 63 MOBILE 0
196 382 R 81 76 1600 C 0 0 False False ... 98 98 998 999999998 998 998 9998 9998 RCC 0
197 384 R 19 19 4000 C 0 0 False False ... 98 98 998 999999998 998 998 9998 9998 IAPS 0
198 385 H 227 40 735 B 0 0 False False ... 98 98 998 999999998 998 998 9998 9998 BRANCH 0
199 386 H 108 12 2500 B 8 9 False False ... 98 98 998 999999998 998 998 9998 9998 IAPS 0

200 rows × 1934 columns