Das deutsche Python-Forum

Code: Alles auswählen

df['Delta_A-B']=df['TI111']-df['TI117']

Code: Alles auswählen

import pandas as pd
import os
import codecs

# Default directory for KDE measurement files
folder = os.path.join('c:', os.sep, 'Users','black cat','OneDrive - Linde Group','APLWT')    
BLOCKSIZE = 1048576  # or some other, desired size in bytes
for file in os.listdir(folder):
    if file.endswith(".TXT") and file.replace('.TXT', '.utf8') not in os.listdir(folder):
        with codecs.open(os.path.join(folder, file), "r", "iso-8859-1") as sourceFile:
            with codecs.open(os.path.join(folder, file.replace('.TXT', '.utf8')), "w", "utf-8") as targetFile:
                while True:
                    contents = sourceFile.read(BLOCKSIZE)
                    if not contents:
                        break
                    targetFile.write(contents)
                    
        # Remove line number 14 (the one with the units after the tag names, as it irritates pd.read_csv)
        f = open(os.path.join(folder, file.replace('.TXT', '.utf8')),"r")
        lines = f.readlines()
        f.close()
        del(lines[13])
        f = open(os.path.join(folder, file.replace('.TXT', '.utf8')),"w")
        for line in lines:
            f.write(line)
        f.close()
        
    
# Read all utf8 logfiles
for file in os.listdir(folder):
    if file.endswith(".utf8"):
        df = pd.read_csv(os.path.join(folder, file),
                             sep='\t', encoding='utf-8', decimal='.', skiprows=12, index_col=False)

        # Create time series
        df['Datetime'] = df['Date']+' '+df['Time']
        df['Datetime'] = df['Datetime'].apply(
            lambda x: pd.to_datetime(x.split(',')[0], format='%d.%m.%Y %H:%M:%S'))
        df = df.set_index('Datetime')
        df = df.drop(columns=['Date', 'Time'])
        
        
   

# Resample to lower frequency
df=df.resample('5S').mean()

Code: Alles auswählen

import matplotlib.pyplot as plt
import datetime as datetime

plt.figure()

df['TI111'].plot()
df['TI112'].plot()
df['TI113'].plot()
df['TI114'].plot()
df['TI115'].plot()
df['TI116'].plot()

plt.legend()
plt.xlabel('Time')
plt.ylabel('Temperature [°C]')