#PARTICULAR CASE
# Import pandas

import pandas as pd


# Import Twitter data as DataFrame: df

df = pd.read_csv('tweets.csv')


# Initialize an empty dictionary: 
langs_count
langs_count = {}


# Extract column from DataFrame: col

col = df['lang']


# Iterate over lang column in DataFrame
for entry in col:
    
# If the language is in langs_count, add 1
    
	if entry in langs_count.keys():
        
		langs_count[entry]=langs_count[entry]+1
    
	# Else add the language to langs_count, set the value to 1
    
	else:
        
		langs_count[entry]=1



# Print the populated dictionary

print(langs_count)

#GENERALIZED CASE
# Define count_entries()

def count_entries(df,col_name):
    
	"""Return a dictionary with counts of 
    occurrences as value for each key."""
    
	# Initialize an empty dictionary: 
	langs_count
    langs_count = {}
    
	# Extract column from DataFrame: col
    
	col = df[col_name]
    
	
	# Iterate over lang column in DataFrame
    
	for entry in col:
        
		# If the language is in langs_count, add 1
        
		if entry in langs_count.keys():
            
			langs_count[entry]=langs_count[entry]+1
        
		# Else add the language to langs_count, set the value to 1

		else:
            
			langs_count[entry]=1

    
	# Return the langs_count dictionary
    
	return langs_count



# Call count_entries(): result

result=count_entries(tweets_df,'lang')


# Print the result

print(result)