# import pandasimport pandas as pd# creating a DataFramepd.DataFrame({ 'Yes': [50, 31], 'No': [101, 2]}) 
# another example of creating a dataframepd.DataFrame({ 'Bob': ['I liked it.', 'It was awful.'], 'Sue': ['Pretty good.', 'Bland']}) 
pd.DataFrame({ 'Bob': ['I liked it.', 'It was awful.'], 'Sue': ['Pretty good.', 'Bland.']}, index = ['Product A', 'Product B']) 
# creating a pandas seriespd.Series([1, 2, 3, 4, 5])
# we can think of a Series as a column of a DataFrame.# we can assign index values to Series in same way as pandas DataFramepd.Series([10, 20, 30], index=['2015 sales', '2016 sales', '2017 sales'], name='Product A')
# reading a csv file and storing it in a variablewine_reviews = pd.read_csv("F:\\kaggleDataSet\\wine-reviews\\winemag-data-130k-v2.csv") # we can use the 'shape' attribute to check size of datasetwine_reviews.shape
# To show first five rows of data, use 'head()' methodwine_reviews.head()
wine_reviews = pd.read_csv("F:\\kaggleDataSet\\wine-reviews\\winemag-data-130k-v2.csv", index_col=0)wine_reviews.head() 
wine_reviews.head().to_csv("F:\\wine_reviews.csv") 
import pandas as pdreviews = pd.read_csv("F:\\kaggleDataSet\\wine-reviews\\winemag-data-130k-v2.csv", index_col=0)pd.set_option("display.max_rows", 5) 
# access 'country' property (or column) of 'reviews' reviews.country
# Another way to do above operation# when a column name contains space, we have to use this methodreviews['country']
# To access first row of country columnreviews['country'][0]
# returns first rowreviews.iloc[0]
# returns first column (country) (all rows due to ':')reviews.iloc[:, 0]
# retruns first 3 rows of first columnreviews.iloc[:3, 0]
# we can pass a list of indices of rows/columns to selectreviews.iloc[[0, 1, 2, 3], 0]
# We can also pass negative numbers as we do in Pythonreviews.iloc[-5:]
# To select first entry in country columnreviews.loc[0, 'country']
# select columns by name using 'loc'reviews.loc[:, ['taster_name', 'taster_twitter_handle', 'points']]
# 'set_index' to the 'title' fieldreviews.set_index('title') 
# 1. Find out whether wine is produced in Italyreviews.country == 'Italy'
# 2. Now select all wines produced in Italyreviews.loc[reviews.country == 'Italy'] #reviews[reviews.country == 'Italy']
# Add one more condition for points to find better than average wines produced in Italyreviews.loc[(reviews.country == 'Italy') & (reviews.points >= 90)] # use | for 'OR' condition
reviews.loc[reviews.country.isin(['Italy', 'France'])]
reviews.loc[reviews.price.notnull()]
reviews['critic'] = 'everyone'reviews.critic
# using iterable for assigningreviews['index_backwards'] = range(len(reviews), 0, -1)reviews['index_backwards']
