<jupyter_start><jupyter_text>Selecting Data using .loc indexer, which uses Label strings Select the Details of Player <NAME><jupyter_code>type(data)
avery_bradley_details = data.loc['Utah Jazz']
avery_bradley_details.Age<jupyter_output><empty_output><jupyter_text>Select the Details of Player <NAME><jupyter_code>r_j_hunter_details = data.loc['<NAME>']
r_j_hunter_details
type(r_j_hunter_details)
data.head()
multi_select_row_cols = data.loc[["<NAME>", "<NAME>"], 
                   ["Team", "Number", "Position"]]
multi_select_row_cols
all_rows_some_cols = data.loc[:, ["Team", "Number", "Position"]] 
all_rows_some_cols<jupyter_output><empty_output><jupyter_text>Selecting Rows and columns using the iloc indexer<jupyter_code>type(data)
type(data.iloc[0])
type(data.Team)
type(data.Team.iloc)
type(data.Team.iloc[0])
data.Team.iloc[100]
data.iloc[0]
i_loc_indexer_data_for_row_3 = data.iloc[0]
i_loc_indexer_data_for_row_3
type(i_loc_indexer_data_for_row_3)
iloc_indexer_for_odd_rows = data.iloc[[3,5,7]]
iloc_indexer_for_odd_rows
type(iloc_indexer_for_odd_rows)
row2 = data.iloc [[3, 4], [1, 2]] 
row2
row3 = data.iloc [:, [1, 2]] 
row3<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1358974358974359, 'fraction_numerical': 0.019658119658119658, 'mean_word_length': 8.293650793650794, 'pattern_counts': {'":': 0, '<': 18, '<?xml version=': 0, '>': 18, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
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