# ---
# data camp example
# ---

# 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] += 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)

# ----------------------
## example 2
# ----------------------
# 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] += 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)

# ---
# example 3 - generalized function
# ----
# Define count_entries()
def count_entries(df, col_name = 'lang'):
    """Return a dictionary with counts of
    occurrences as value for each key."""

    # Initialize an empty dictionary: cols_count
    cols_count = {}

    # Extract column from DataFrame: col
    col = df[col_name]

    # Iterate over the column in DataFrame
    for entry in col:

        # If entry is in cols_count, add 1
        if entry in cols_count.keys():
            cols_count[entry] += 1

        # Else add the entry to cols_count, set the value to 1
        else:
            cols_count[entry] = 1

    # Return the cols_count dictionary
    return cols_count

# Call count_entries(): result1
result1 = count_entries(tweets_df)

# Call count_entries(): result2
result2 = count_entries(tweets_df, 'source')

# Print result1 and result2
print(result1)
print(result2)