import pandas as pd
import numpy as np

# Create a simple Series from a list of values; default integer index is used
data = [10, 20, 30, 40, 50]
series_1 = pd.Series(data)
print(f"series_1: Series from a list: {data}")
print(series_1)
print()

#   An empty series.
series_2 = pd.Series()
print("series_2: empty series: []")
print(series_2)
print()

#   A series with custom labels/indices.
test_data = [90, 77, 90]
test_index = ["test_1", "test_2", "test_3"]
series_3 = pd.Series(test_data, index=test_index)
print(f"series_3: explicitly labeled series.")
print(f"element values: {test_data}")
print(f"custom index: {test_index}")
print(series_3)
print()

#   A series with custom labels/indices and a 'not a number' value (np.nan)
test_data = [90, 77, 90, np.nan]
test_index = ["test_1", "test_2", "test_3", "test_4"]
series_4 = pd.Series(test_data, index=test_index)
print(f"series_4: explicitly labeled series.")
print(f"element values: {test_data}")
print(f"custom index: {test_index}")
print(series_4)
print()

#   Example methods of Series
print(f"series_4.head(): {series_4.head()}")
print()
print(f"series_4.describe(): {series_4.describe()}")
print()
print(f"series_4.value_counts(): {series_4.value_counts()}")
print()
print(f"series_4.sort_values():\n{series_4.sort_values()}")
print()
print(f"series_4:\n{series_4}")
print()
print(f"series_4.dropna():\n{series_4.dropna()}")
print()
print(f"series_4:\n{series_4}")