<jupyter_start><jupyter_text>FANCY İNDEX YAKLASIMI<jupyter_code>seri[["ebru","metin"]]
seri["ebru":"cat"]<jupyter_output><empty_output><jupyter_text>DATAFRAME LAR<jupyter_code>l = np.arange(0,9).reshape((3,3))
l
df = pd.DataFrame(l, columns=["col1","col2","col3"])
df
df.columns= ("met1","met2","met3")
df
df
type(df)
df.axes
df.shape
df.ndim
df.values
type(df.values)
df.head(0)
aku = np.array([10,20,30,40,50])
pd.DataFrame(aku, columns= ["metin"])<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.21666666666666667, 'fraction_numerical': 0.04375, 'mean_word_length': 10.452380952380953, 'pattern_counts': {'":': 1, '<': 9, '<?xml version=': 0, '>': 9, '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}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '637882', 'license': 'BSD-2-Clause', 'n_tokens_mistral': 234, 'n_tokens_neox': 228, 'n_words': 27, 'path': 'FRAMEVORKS OLUSTURMA.ipynb', 'repo_name': 'matua34/Veri-Gorsellestirme', 'size': '480'}