I have reinstalled the anaconda after formatting my machine, since I am getting error while opening the files in jupyter notebook.
Initially I tried access the file from desktop location, as I got an error again tried to access from D drive. both were not successful attempts.
salaries = pd.read_excel('D:\\housesales.xlsx')
Below is the error
FileNotFoundError Traceback (most recent call last) <ipython-input-13-6d8e17cbb085> in <module> ----> 1 salaries = pd.read_excel('D:\housesales.xlsx') ~\Anaconda3\lib\site-packages\pandas\util_decorators.py in wrapper(*args, **kwargs) 186 else: 187 kwargs[new_arg_name] = new_arg_value --> 188 return func(*args, **kwargs) 189 return wrapper 190 return _deprecate_kwarg ~\Anaconda3\lib\site-packages\pandas\util_decorators.py in wrapper(*args, **kwargs) 186 else: 187 kwargs[new_arg_name] = new_arg_value --> 188 return func(*args, **kwargs) 189 return wrapper 190 return _deprecate_kwarg ~\Anaconda3\lib\site-packages\pandas\io\excel.py in read_excel(io, sheet_name, header, names, index_col, parse_cols, usecols, squeeze, dtype, engine, converters, true_values, false_values, skiprows, nrows, na_values, keep_default_na, verbose, parse_dates, date_parser, thousands, comment, skip_footer, skipfooter, convert_float, mangle_dupe_cols, **kwds) 348 349 if not isinstance(io, ExcelFile): --> 350 io = ExcelFile(io, engine=engine) 351 352 return io.parse( ~\Anaconda3\lib\site-packages\pandas\io\excel.py in init(self, io, engine) 651 self._io = _stringify_path(io) 652 --> 653 self._reader = self._enginesengine 654 655 def fspath(self): ~\Anaconda3\lib\site-packages\pandas\io\excel.py in init(self, filepath_or_buffer) 422 self.book = xlrd.open_workbook(file_contents=data) 423 elif isinstance(filepath_or_buffer, compat.string_types): --> 424 self.book = xlrd.open_workbook(filepath_or_buffer) 425 else: 426 raise ValueError('Must explicitly set engine if not passing in' ~\Anaconda3\lib\site-packages\xlrd__init__.py in open_workbook(filename, logfile, verbosity, use_mmap, file_contents, encoding_override, formatting_info, on_demand, ragged_rows) 109 else: 110 filename = os.path.expanduser(filename) --> 111 with open(filename, "rb") as f: 112 peek = f.read(peeksz) 113 if peek == b"PK\x03\x04": # a ZIP file FileNotFoundError: [Errno 2] No such file or directory: 'D:\housesales.xlsx'
Sounds like your housesales.xlsx file is on your Desktop, but you do not include the Desktop folder in the path to your file.
salaries = pd.read_excel('D:\\Desktop\housesales.xlsx')
I recommend you use jupyter lab as it has a file tree.
Running this bash command in a notebook cell will tell you the working directory of your jupyter instance so you know where it is looking for files.
!pwd
You could also move your file to that directory and then just access it as
salaries = pd.read_excel('housesales.xlsx')
Related
When i run pip3 install <package> or !pip3 install <package> or !pip install <package> i get this error. And also i can't clone any repo in jupyter. It gives the same error. This is my first time in Jupyter.
---------------------------------------------------------------------------
OSError Traceback (most recent call last)
Input In [18], in <cell line: 1>()
----> 1 get_ipython().run_line_magic('pip', 'install boto3')
File /lib/python3.9/site-packages/IPython/core/interactiveshell.py:2294, in InteractiveShell.run_line_magic(self, magic_name, line, _stack_depth)
2292 kwargs['local_ns'] = self.get_local_scope(stack_depth)
2293 with self.builtin_trap:
-> 2294 result = fn(*args, **kwargs)
2295 return result
File /lib/python3.9/site-packages/IPython/core/magics/packaging.py:75, in PackagingMagics.pip(self, line)
72 else:
73 python = shlex.quote(python)
---> 75 self.shell.system(" ".join([python, "-m", "pip", line]))
77 print("Note: you may need to restart the kernel to use updated packages.")
File /lib/python3.9/site-packages/IPython/core/interactiveshell.py:2451, in InteractiveShell.system_piped(self, cmd)
2446 raise OSError("Background processes not supported.")
2448 # we explicitly do NOT return the subprocess status code, because
2449 # a non-None value would trigger :func:`sys.displayhook` calls.
2450 # Instead, we store the exit_code in user_ns.
-> 2451 self.user_ns['_exit_code'] = system(self.var_expand(cmd, depth=1))
File /lib/python3.9/site-packages/IPython/utils/_process_posix.py:148, in ProcessHandler.system(self, cmd)
146 child = pexpect.spawnb(self.sh, args=['-c', cmd]) # Pexpect-U
147 else:
--> 148 child = pexpect.spawn(self.sh, args=['-c', cmd]) # Vanilla Pexpect
149 flush = sys.stdout.flush
150 while True:
151 # res is the index of the pattern that caused the match, so we
152 # know whether we've finished (if we matched EOF) or not
File /lib/python3.9/site-packages/IPython/utils/_process_posix.py:57, in ProcessHandler.sh(self)
55 self._sh = pexpect.which(shell_name)
56 if self._sh is None:
---> 57 raise OSError('"{}" shell not found'.format(shell_name))
59 return self._sh
I searched everywhere, but it is weird that no-one faced this issue except me. Pls provide some solution for this. I'm getting crazy.
I have the following code taken directly from here with some pretty little modifications:
import pandas as pd
import torch
import json
from transformers import T5Tokenizer, T5ForConditionalGeneration, T5Config
from torch import cuda
df = pd.read_pickle('df_final.pkl')
model = T5ForConditionalGeneration.from_pretrained('t5-base')
tokenizer = T5Tokenizer.from_pretrained('t5-base')
device = 'cuda' if cuda.is_available() else 'cpu'
text = ''.join(df[(df['col1'] == 'type') & (df['col2'] == 2)].col3.to_list())
preprocess_text = text.strip().replace("\n","")
t5_prepared_Text = "summarize: "+preprocess_text
#print ("original text preprocessed: \n", preprocess_text)
tokenized_text = tokenizer.encode(t5_prepared_Text, return_tensors="pt", max_length = 500000).to(device)
# summmarize
summary_ids = model.generate(tokenized_text,
num_beams=4,
no_repeat_ngram_size=2,
min_length=30,
max_length=100,
early_stopping=True)
output = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
print ("\n\nSummarized text: \n",output)
When executing the model_generate() part i get an error like this:
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
<ipython-input-12-e8e9819a85dc> in <module>
12 min_length=30,
13 max_length=100,
---> 14 early_stopping=True).to(device)
15
16 output = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
~\Anaconda3\lib\site-packages\torch\autograd\grad_mode.py in decorate_no_grad(*args, **kwargs)
47 def decorate_no_grad(*args, **kwargs):
48 with self:
---> 49 return func(*args, **kwargs)
50 return decorate_no_grad
51
~\Anaconda3\lib\site-packages\transformers\generation_utils.py in generate(self, input_ids, max_length, min_length, do_sample, early_stopping, num_beams, temperature, top_k, top_p, repetition_penalty, bad_words_ids, bos_token_id, pad_token_id, eos_token_id, length_penalty, no_repeat_ngram_size, num_return_sequences, attention_mask, decoder_start_token_id, use_cache, **model_specific_kwargs)
383 encoder = self.get_encoder()
384
--> 385 encoder_outputs: tuple = encoder(input_ids, attention_mask=attention_mask)
386
387 # Expand input ids if num_beams > 1 or num_return_sequences > 1
~\Anaconda3\lib\site-packages\torch\nn\modules\module.py in __call__(self, *input, **kwargs)
539 result = self._slow_forward(*input, **kwargs)
540 else:
--> 541 result = self.forward(*input, **kwargs)
542 for hook in self._forward_hooks.values():
543 hook_result = hook(self, input, result)
~\Anaconda3\lib\site-packages\transformers\modeling_t5.py in forward(self, input_ids, attention_mask, encoder_hidden_states, encoder_attention_mask, inputs_embeds, head_mask, past_key_value_states, use_cache, output_attentions, output_hidden_states, return_dict)
701 if inputs_embeds is None:
702 assert self.embed_tokens is not None, "You have to intialize the model with valid token embeddings"
--> 703 inputs_embeds = self.embed_tokens(input_ids)
704
705 batch_size, seq_length = input_shape
~\Anaconda3\lib\site-packages\torch\nn\modules\module.py in __call__(self, *input, **kwargs)
539 result = self._slow_forward(*input, **kwargs)
540 else:
--> 541 result = self.forward(*input, **kwargs)
542 for hook in self._forward_hooks.values():
543 hook_result = hook(self, input, result)
~\Anaconda3\lib\site-packages\torch\nn\modules\sparse.py in forward(self, input)
112 return F.embedding(
113 input, self.weight, self.padding_idx, self.max_norm,
--> 114 self.norm_type, self.scale_grad_by_freq, self.sparse)
115
116 def extra_repr(self):
~\Anaconda3\lib\site-packages\torch\nn\functional.py in embedding(input, weight, padding_idx, max_norm, norm_type, scale_grad_by_freq, sparse)
1482 # remove once script supports set_grad_enabled
1483 _no_grad_embedding_renorm_(weight, input, max_norm, norm_type)
-> 1484 return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
1485
1486
RuntimeError: Expected object of device type cuda but got device type cpu for argument #1 'self' in call to _th_index_select
I've searched this error and fouund some other threads like this one and this one but they didn't help me much since their case seems to be completely different. In my case there are no custom instances or classes created, so i don't know how to fix this or where the error come from.
Could you please tell me where is the error coming from and how could i fix it?
Thank you very much in advance.
Try explicitly moving your model to the GPU.
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
model = T5ForConditionalGeneration.from_pretrained('t5-base').to(device)
In the recent VS Code release, they added this feature to view the active variables in the Jupyter Notebook and also, view the values in the variable with Data Viewer.
However, every time I am trying to view the values in Data Viewer, VS Code is throwing error below. It says that the reason is that the object of data type is Int64 and not string, but I am sure that should not be the reason to not show the variable. Anyone facing similar issues. I tried with a simple data frame and it's working fine.
Error: Failure during variable extraction:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-16-eae5f1f55b35> in <module>
97
98 # Transform this back into a string
---> 99 print(_VSCODE_json.dumps(_VSCODE_targetVariable))
100 del _VSCODE_targetVariable
101
~/anaconda3/lib/python3.7/json/__init__.py in dumps(obj, skipkeys, ensure_ascii, check_circular, allow_nan, cls, indent, separators, default, sort_keys, **kw)
229 cls is None and indent is None and separators is None and
230 default is None and not sort_keys and not kw):
--> 231 return _default_encoder.encode(obj)
232 if cls is None:
233 cls = JSONEncoder
~/anaconda3/lib/python3.7/json/encoder.py in encode(self, o)
197 # exceptions aren't as detailed. The list call should be roughly
198 # equivalent to the PySequence_Fast that ''.join() would do.
--> 199 chunks = self.iterencode(o, _one_shot=True)
200 if not isinstance(chunks, (list, tuple)):
201 chunks = list(chunks)
~/anaconda3/lib/python3.7/json/encoder.py in iterencode(self, o, _one_shot)
255 self.key_separator, self.item_separator, self.sort_keys,
256 self.skipkeys, _one_shot)
--> 257 return _iterencode(o, 0)
258
259 def _make_iterencode(markers, _default, _encoder, _indent, _floatstr,
~/anaconda3/lib/python3.7/json/encoder.py in default(self, o)
177
178 """
--> 179 raise TypeError(f'Object of type {o.__class__.__name__} '
180 f'is not JSON serializable')
181
TypeError: Object of type int64 is not JSON serializable
The library expects utf-8. I tried to convert my us-ascii file to utf-8 using:
iconv -f us-ascii -t utf-8 src.csv > target.csv
When I did:
file -I target.csv
It still showed charset as us-ascii. Then I found out that us-ascii is a subset of utf-8 and that file will only guess the file type.
However, if I take use src.csv as input to the TextLMDataBunch.from_csv() library, it works. If I do:
cat src.csv > target.csv
And then use target.csv as input to the same library, it doesn't work and gives the following error:
TypeError Traceback (most recent call last)
<ipython-input-118-44bc7147d2a4> in <module>()
----> 1 data_lm = TextLMDataBunch.from_csv(sample_p, 'voila.csv')
/usr/local/lib/python3.6/dist-packages/fastai/text/data.py in from_csv(cls, path, csv_name, valid_pct, test, tokenizer, vocab, classes, header, text_cols, label_cols, label_delim, **kwargs)
180 test_df = None if test is None else pd.read_csv(Path(path)/test, header=header)
181 return cls.from_df(path, train_df, valid_df, test_df, tokenizer, vocab, classes, text_cols,
--> 182 label_cols, label_delim, **kwargs)
183
184 #classmethod
/usr/local/lib/python3.6/dist-packages/fastai/text/data.py in from_df(cls, path, train_df, valid_df, test_df, tokenizer, vocab, classes, text_cols, label_cols, label_delim, **kwargs)
165 src = ItemLists(path, TextList.from_df(train_df, path, cols=text_cols, processor=processor),
166 TextList.from_df(valid_df, path, cols=text_cols, processor=processor))
--> 167 src = src.label_for_lm() if cls==TextLMDataBunch else src.label_from_df(cols=label_cols, classes=classes, sep=label_delim)
168 if test_df is not None: src.add_test(TextList.from_df(test_df, path, cols=text_cols))
169 return src.databunch(**kwargs)
/usr/local/lib/python3.6/dist-packages/fastai/data_block.py in _inner(*args, **kwargs)
356 assert isinstance(fv, Callable)
357 def _inner(*args, **kwargs):
--> 358 self.train = ft(*args, **kwargs)
359 assert isinstance(self.train, LabelList)
360 self.valid = fv(*args, **kwargs)
/usr/local/lib/python3.6/dist-packages/fastai/text/data.py in label_for_lm(self, **kwargs)
285 "A special labelling method for language models."
286 self.__class__ = LMTextList
--> 287 return self.label_const(0, label_cls=LMLabel)
288
289 def reconstruct(self, t:Tensor):
/usr/local/lib/python3.6/dist-packages/fastai/data_block.py in label_const(self, const, **kwargs)
211 def label_const(self, const:Any=0, **kwargs)->'LabelList':
212 "Label every item with `const`."
--> 213 return self.label_from_func(func=lambda o: const, **kwargs)
214
215 def label_empty(self):
/usr/local/lib/python3.6/dist-packages/fastai/data_block.py in label_from_func(self, func, **kwargs)
219 def label_from_func(self, func:Callable, **kwargs)->'LabelList':
220 "Apply `func` to every input to get its label."
--> 221 return self.label_from_list([func(o) for o in self.items], **kwargs)
222
223 def label_from_folder(self, **kwargs)->'LabelList':
TypeError: iteration over a 0-d array
Can someone please tell me what is wrong? I am trying this on Google Colab and tried the character encoding changes on Colab and on my Mac but with no results.
I am developing Python 3.5.3 using the jupyter notebook in Anaconda 2.5.0 (64-bit) on a Windows 10 machine. I am trying to use an extension called 'gvmagic', which is used for viewing graphs. The extension seems to load, but returns a FileNotFoundError instead of a graph.
My input code is (Note: 'visualize_de_bruijn_graph' is a custom code that builds a de Bruijn graph from a string):
dbg = visualize_de_bruijn_graph('ACGCGTCG', 3)
print(dbg)
Which returns graph:
digraph "DeBruijn Graph" {
CG [label="CG"] ;
TC [label="TC"] ;
GC [label="GC"] ;
AC [label="AC"] ;
GT [label="GT"] ;
AC -> CG ;
CG -> GC ;
GC -> CG ;
CG -> GT ;
GT -> TC ;
TC -> CG ;
}
Trying to visualize the graph with the following code:
%load_ext gvmagic
%dotstr dbg
returns the error below. I cannot figure out what file is missing, as all the files referenced are where they are suppose to be.
FileNotFoundError Traceback (most recent call last)
<ipython-input-17-d138faf6c47c> in <module>()
----> 1 get_ipython().magic('dotstr dbg')
C:\Users\username\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py in magic(self, arg_s)
2161 magic_name, _, magic_arg_s = arg_s.partition(' ')
2162 magic_name = magic_name.lstrip(prefilter.ESC_MAGIC)
-> 2163 return self.run_line_magic(magic_name, magic_arg_s)
2164
2165 #-------------------------------------------------------------------------
C:\Users\username\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py in run_line_magic(self, magic_name, line)
2082 kwargs['local_ns'] = sys._getframe(stack_depth).f_locals
2083 with self.builtin_trap:
-> 2084 result = fn(*args,**kwargs)
2085 return result
2086
<decorator-gen-126> in dotstr(self, line)
C:\Users\username\Anaconda3\lib\site-packages\IPython\core\magic.py in <lambda>(f, *a, **k)
191 # but it's overkill for just that one bit of state.
192 def magic_deco(arg):
--> 193 call = lambda f, *a, **k: f(*a, **k)
194
195 if callable(arg):
C:\Users\username\Anaconda3\lib\site-packages\IPython\extensions\gvmagic.py in dotstr(self, line)
50 #line_magic
51 def dotstr(self, line):
---> 52 self._from_str(line, 'dot')
53
54 #line_magic
C:\Users\username\Anaconda3\lib\site-packages\IPython\extensions\gvmagic.py in _from_str(self, line, layout_engine)
151 def _from_str(self, line, layout_engine):
152 s = self.shell.ev(line)
--> 153 data = run_graphviz(s, layout_engine)
154 if data:
155 display_svg(data, raw=True)
C:\Users\username\Anaconda3\lib\site-packages\IPython\extensions\gvmagic.py in run_graphviz(s, layout_engine)
30 cmd = ['dot', '-Tsvg', '-K', layout_engine]
31
---> 32 dot = Popen(cmd, stdin=PIPE, stdout=PIPE, stderr=PIPE)
33 stdoutdata, stderrdata = dot.communicate(s.encode('utf-8'))
34 status = dot.wait()
C:\Users\username\Anaconda3\lib\subprocess.py in __init__(self, args, bufsize, executable, stdin, stdout, stderr, preexec_fn, close_fds, shell, cwd, env, universal_newlines, startupinfo, creationflags, restore_signals, start_new_session, pass_fds)
674 c2pread, c2pwrite,
675 errread, errwrite,
--> 676 restore_signals, start_new_session)
677 except:
678 # Cleanup if the child failed starting.
C:\Users\username\Anaconda3\lib\subprocess.py in _execute_child(self, args, executable, preexec_fn, close_fds, pass_fds, cwd, env, startupinfo, creationflags, shell, p2cread, p2cwrite, c2pread, c2pwrite, errread, errwrite, unused_restore_signals, unused_start_new_session)
953 env,
954 cwd,
--> 955 startupinfo)
956 finally:
957 # Child is launched. Close the parent's copy of those pipe
FileNotFoundError: [WinError 2] The system cannot find the file specified
You have to install the Graphviz software on your PC. For Windows, for example, download this https://graphviz.gitlab.io/_pages/Download/Download_windows.html.
In your IPython session, you have to point to the install location, for example:
import os
os.environ["PATH"] += os.pathsep + 'C:/Program Files (x86)/Graphviz2.38/bin'
%load_ext gvmagic
dbg = visualize_de_bruijn('ACGCGTCG', 3)
%dotstr dbg
And now it should work for you, just as it does for me! You can probably set the PATH variable on your PC instead of having to do it inside IPython each time.