Input, Subset and Output External Data Files using Pandas

# Print the working directory
import os
print os.getcwd()
# C:\Python27\Scripts

# Set the working directory
os.chdir('C:/Users/general1/Documents/simple Python files')
print os.getcwd()
# C:\Users\general1\Documents\simple Python files

# load pandas
import pandas as pd

# read a csv data file named 'small_dataset.csv' containing 4 lines and 3 variables
my_data = pd.read_csv("small_dataset.csv")
my_data
#     x   y   z
# 0   1   2   3
# 1   4   5   6
# 2   7   8   9
# 3  10  11  12

my_data.shape       # number of rows and columns in data set
# (4, 3)

my_data.shape[0]    # number of rows in data set
# 4

my_data.shape[1]    # number of columns in data set
# 3

# Python uses 0-based indexing.  The first row or column in a data set is located
# at position 0.  In R the first row or column in a data set is located
# at position 1.

# Select the first two rows
my_data[0:2]
#    x   y   z
#0   1   2   3
#1   4   5   6

# Select the second and third rows
my_data[1:3]
#    x  y  z
# 1  4  5  6
# 2  7  8  9

# Select the third row
my_data[2:3]
#    x   y   z
#2   7   8   9

# Select the first two elements of the first column
my_data.iloc[0:2, 0:1]
#    x
# 0  1
# 1  4

# Select the first element of the variables y and z
my_data.loc[0, ['y', 'z']]
# y    2
# z    3

# Select the first three elements of the variables y and z
my_data.loc[0:2, ['y', 'z']]
#    y  z
# 0  2  3
# 1  5  6
# 2  8  9

# Write the first three elements of the variables y and z
# to an external file.  Here index = 0 means do not write row names.

my_data2 = my_data.loc[0:2, ['y', 'z']]

my_data2.to_csv('my.output.csv', index = 0)