FileNotFoundError: [Errno2] No such file or directory: 'in_out_put/live_data.csv' How do I work?

#9 Import various libraries
print("[Start Import Library]")
import numpy as np
import pandas aspd
import tensorflow as tf
# from tensorflow.keras.models import load_model, Model
from keras.models import load_model, Model
print("[Library Import Complete]")
​
m_recent=24# 要Adjustment required 調整Number of legs to be used for prediction (based on past 24 legs)
​
# 直 Preparation of the latest price movement data
print("[Last price movement data read start]US>")# Display load start
data=pd.read_csv("in_out_put/live_data.csv", encoding="shift-jis")# [Adjustment Required] Read the most recent price movement data
data=data.loc[:,["Low", "Close", "High"]]# Extract all rows (:) and columns only "Low", "Close", and "High"
X = [ ] # First, prepare an empty X box
print("[Last price movement data read completed]US>")# Display load completion
​
print("[Recent price movement data construction start]US>")#Displays the start of data construction to be entered into AI
X.append(data.loc[len(data)-m_recent:(len(data))], ["Low", "Close", "High"]])# Add values of "Low", "Close", and "High" from last line to 24 lines to X  
X_live=np.array(X)# Generate numpy array
print(X_live)# Show X_live
print("[Last price movement data construction completed]US>")# Display completion of data construction to be entered into AI
​
# 学習 Load Learned AI
print("[Start loading learned AI]US>")# Display learned AI load start
model=load_model('in_out_put/model_epochs_10.h5')# [Adjustment Required] Load saved learned AI
print("[Learned AI Load Completed]US>")# View Learned AI Load Complete
​
# 直 Performing predictions using the most recent data
print("[Start prediction using the most recent price movement data]")
predicted=model.predict(X_live)#X_live as input for prediction
print("[Prediction completed using the latest price movement data]")
​
# 予測 Viewing Forecast Results
print("================================================")# Display horizontal lines of decoration
if predicated [0,0]>=0.5: # When the probability of rising is 50% or higher
    print("Predicted results:", '{:4g}'.format(predicted[0,0]*100), "% chance of rising") # 4 valid digits → {:4g} to show certainty
else: # When you're more than 50% sure you'llow
    print("Predicted results:", '{:4g}'.format(predicted[0,1]*100), "% chance to drop") # 4 valid digits → {:4g} to show certainty
print("================================================")# Display horizontal lines of decoration

[Start importing libraries]
Library Import Complete
[Recent price movement data read]
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
<ipython-input-2-80fce524d42d>in<module>
     12# 直 Preparation of the most recent price movement data
     13 print("[Last price movement data read start]US>")# Display load start
--->14 data=pd.read_csv("in_out_put/live_data.csv", encoding="shift-jis")#[Adjustment Required] Read the most recent price movement data
     15 data=data.loc[:,["Low", "Close", "High"]]# Extract all rows (:) and only three columns are "Low", "Close", and "High"
     16 X = [ ] # First, prepare an empty X box

~\anaconda3\envs\ai_aki_maki\lib\site-packages\pandas\io\parsers.py in read_csv(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetimage_format, keep_date_col, date_parser, dayfirst, cache_dates, iterator, chunksize, compression, thousands, critical, lineterminator, quote, double quote, escapecar, comment, encoding, error_body_loads, word_loads, word_loads, word_loads, word
    686     )
    687 
-->688 return_read (filepath_or_buffer, kwds)
    689 
    690 

~\anaconda3\envs\ai_aki_maki\lib\site-packages\pandas\io\parsers.py in_read (filepath_or_buffer, kwds)
    452 
    453#Create the parser.
-->454 parser=TextFileReader(fp_or_buf,**kwds)
    455 
    456 if chunksize oriterator:

~\anaconda3\envs\ai_aki_maki\lib\site-packages\pandas\io\parsers.py in __init__(self, f, engine, **kwds)
    946self.options["has_index_names"] = kwds["has_index_names"]
    947 
-->948self._make_engine(self.engine)
    949 
    950 def close (self):

~\anaconda3\envs\ai_aki_maki\lib\site-packages\pandas\io\parsers.py in_make_engine(self,engine)
   1178 def_make_engine(self, engine="c"):
   1179 if engine=="c":
->1180self._engine=CParserWrapper (self.f,**self.options)
   1181 else:
   1182 if engine=="python":

~\anaconda3\envs\ai_aki_maki\lib\site-packages\pandas\io\parsers.py in_init__(self, src, **kwds)
   1991 if kwds.get ("compression") is None and encoding:
   1992 if isinstance(src, str):
- > 1993 src = open(src, "rb")
   1994 self.handles.append(src)
   1995 

FileNotFoundError: [Errno2] No such file or directory: 'in_out_put/live_data.csv'
'''