pandas_exemple.py

import os
import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
import matplotlib.pyplot as plt
import seaborn as sns
from matplotlib import style
style.use("ggplot")

data = pd.read_csv('input/pokemon.csv')

series = data['Defense']        # data['Defense'] = series
print(type(series))
data_frame = data[['Defense']]  # data[['Defense']] = data frame
print(type(data_frame))

# 1 - Filtering Pandas data frame
x = data['Defense']>200     # There are only 3 pokemons who have higher defense value than 200
print(data[x])

# 2 - Filtering pandas with logical_and
# There are only 2 pokemons who have higher defence value than 2oo and higher attack value than 100
x = data[np.logical_and(data['Defense']>200, data['Attack']>100 )]
print(x)

# This is also same with previous code line. Therefore we can also use '&' for filtering.
data[(data['Defense']>200) & (data['Attack']>100)]