Hi,how do I merge .txt file date and time column?

Hi,Need to merge date and time columns in one.Thank you!

Answer 1

[Star Strider]

Try something like this —

T1 = readtable('https://www.mathworks.com/matlabcentral/answers/uploaded_files/1238782/IMM2211.txt', 'VariableNamingRule','preserve')

T1 = 2880×18 table
    Contributor:       National       Oceanography    Centre,    Liverpool    Var6    Var7    Var8    Var9    Var10    Var11    Var12    Var13    Var14    Var15    Var16    Var17    Var18
    ____________    ______________    ____________    _______    _________    ____    ____    ____    ____    _____    _____    _____    _____    _____    _____    _____    _____    _____

      {'1)' }       {'2022/11/01'}      00:00:00       5.616       0.293      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'2)' }       {'2022/11/01'}      00:15:00       5.381       0.267      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'3)' }       {'2022/11/01'}      00:30:00        5.13       0.243      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'4)' }       {'2022/11/01'}      00:45:00       4.876       0.229      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'5)' }       {'2022/11/01'}      01:00:00        4.61       0.215      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'6)' }       {'2022/11/01'}      01:15:00       4.345       0.207      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'7)' }       {'2022/11/01'}      01:30:00       4.093       0.212      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'8)' }       {'2022/11/01'}      01:45:00        3.86       0.229      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'9)' }       {'2022/11/01'}      02:00:00       3.637       0.244      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'10)'}       {'2022/11/01'}      02:15:00       3.426       0.255      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'11)'}       {'2022/11/01'}      02:30:00       3.227       0.259      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'12)'}       {'2022/11/01'}      02:45:00       3.039       0.253      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'13)'}       {'2022/11/01'}      03:00:00       2.867       0.242      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'14)'}       {'2022/11/01'}      03:15:00       2.727        0.24      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'15)'}       {'2022/11/01'}      03:30:00       2.622        0.25      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'16)'}       {'2022/11/01'}      03:45:00       2.535       0.256      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 

DateTime = datetime(T1.National, 'InputFormat','yyyy/MM/dd') + timeofday(datetime(string(T1.Oceanography)));
T1 = addvars(T1, DateTime, 'Before',2)

T1 = 2880×19 table
    Contributor:          DateTime             National       Oceanography    Centre,    Liverpool    Var6    Var7    Var8    Var9    Var10    Var11    Var12    Var13    Var14    Var15    Var16    Var17    Var18
    ____________    ____________________    ______________    ____________    _______    _________    ____    ____    ____    ____    _____    _____    _____    _____    _____    _____    _____    _____    _____

      {'1)' }       01-Nov-2022 00:00:00    {'2022/11/01'}      00:00:00       5.616       0.293      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'2)' }       01-Nov-2022 00:15:00    {'2022/11/01'}      00:15:00       5.381       0.267      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'3)' }       01-Nov-2022 00:30:00    {'2022/11/01'}      00:30:00        5.13       0.243      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'4)' }       01-Nov-2022 00:45:00    {'2022/11/01'}      00:45:00       4.876       0.229      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'5)' }       01-Nov-2022 01:00:00    {'2022/11/01'}      01:00:00        4.61       0.215      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'6)' }       01-Nov-2022 01:15:00    {'2022/11/01'}      01:15:00       4.345       0.207      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'7)' }       01-Nov-2022 01:30:00    {'2022/11/01'}      01:30:00       4.093       0.212      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'8)' }       01-Nov-2022 01:45:00    {'2022/11/01'}      01:45:00        3.86       0.229      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'9)' }       01-Nov-2022 02:00:00    {'2022/11/01'}      02:00:00       3.637       0.244      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'10)'}       01-Nov-2022 02:15:00    {'2022/11/01'}      02:15:00       3.426       0.255      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'11)'}       01-Nov-2022 02:30:00    {'2022/11/01'}      02:30:00       3.227       0.259      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'12)'}       01-Nov-2022 02:45:00    {'2022/11/01'}      02:45:00       3.039       0.253      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'13)'}       01-Nov-2022 03:00:00    {'2022/11/01'}      03:00:00       2.867       0.242      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'14)'}       01-Nov-2022 03:15:00    {'2022/11/01'}      03:15:00       2.727        0.24      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'15)'}       01-Nov-2022 03:30:00    {'2022/11/01'}      03:30:00       2.622        0.25      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 
      {'16)'}       01-Nov-2022 03:45:00    {'2022/11/01'}      03:45:00       2.535       0.256      NaN     NaN     NaN     NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN      NaN 

It creates a new variable called ‘DateTime’ and then inserts it as the second variable.

.

[kolberg]

Hey Star,

Now I cant omit the Ms next to the numbers in the txt file.Then it shows as NaN in T1.

[Star Strider]

I didn’t look at the file first. I trusted readtable to guess correctly what was in the file, and readtable guessed in error. So, this time I’m reading it as a cell array, and then converting. (There are non-numeric entries in the last two columns, so they can’t be converted to numeric vectors.)

Try this —

C1 = readcell('https://www.mathworks.com/matlabcentral/answers/uploaded_files/1238782/IMM2211.txt')

C1 = 2891×18 cell array
    {'Port:'       }    {'P026'        }    {1×1 missing         }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'Site:'       }    {'Immingham'   }    {1×1 missing         }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'Latitude:'   }    {[     53.6310]}    {1×1 missing         }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'Longitude:'  }    {[     -0.1860]}    {1×1 missing         }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'Start'       }    {'Date:'       }    {'01NOV2022-00.00.00'}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'End'         }    {'Date:'       }    {'30NOV2022-23.45.00'}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'Contributor:'}    {'National'    }    {'Oceanography'      }    {'Centre,'  }    {'Liverpool'}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'Datum'       }    {'information:'}    {'The'               }    {'data'     }    {'refer'    }    {'to'       }    {'Admiralty'   }    {'Chart'    }    {'Datum'    }    {'(ACD)'    }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'Parameter'   }    {'code:'       }    {'ASLVBG02'          }    {'='        }    {'Surface'  }    {'elevation'}    {'(unspecified'}    {'datum)'   }    {'of'       }    {'the'      }    {'water'    }    {'body'     }    {'by'       }    {'bubbler'  }    {'tide'     }    {'gauge'    }    {'(second'  }    {'sensor)'  }
    {'Cycle'       }    {'Date'        }    {'Time'              }    {'ASLVBG02' }    {'Residual' }    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'Number'      }    {'yyyy'        }    {'mm'                }    {'dd'       }    {'hh'       }    {'mi'       }    {'ssf'         }    {'f'        }    {'f'        }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'1)'          }    {'2022/11/01'  }    {[00:00:00          ]}    {[   5.6160]}    {[   0.2930]}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'2)'          }    {'2022/11/01'  }    {[00:15:00          ]}    {[   5.3810]}    {[   0.2670]}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'3)'          }    {'2022/11/01'  }    {[00:30:00          ]}    {[   5.1300]}    {[   0.2430]}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'4)'          }    {'2022/11/01'  }    {[00:45:00          ]}    {[   4.8760]}    {[   0.2290]}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'5)'          }    {'2022/11/01'  }    {[01:00:00          ]}    {[   4.6100]}    {[   0.2150]}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}

T1 = cell2table(C1(12:end,1:5));
T1.Properties.VariableNames = C1(10, 1:5)

T1 = 2880×5 table
     Cycle          Date           Time       ASLVBG02      Residual 
    _______    ______________    ________    __________    __________

    {'1)' }    {'2022/11/01'}    00:00:00    {[5.6160]}    {[0.2930]}
    {'2)' }    {'2022/11/01'}    00:15:00    {[5.3810]}    {[0.2670]}
    {'3)' }    {'2022/11/01'}    00:30:00    {[5.1300]}    {[0.2430]}
    {'4)' }    {'2022/11/01'}    00:45:00    {[4.8760]}    {[0.2290]}
    {'5)' }    {'2022/11/01'}    01:00:00    {[4.6100]}    {[0.2150]}
    {'6)' }    {'2022/11/01'}    01:15:00    {[4.3450]}    {[0.2070]}
    {'7)' }    {'2022/11/01'}    01:30:00    {[4.0930]}    {[0.2120]}
    {'8)' }    {'2022/11/01'}    01:45:00    {[3.8600]}    {[0.2290]}
    {'9)' }    {'2022/11/01'}    02:00:00    {[3.6370]}    {[0.2440]}
    {'10)'}    {'2022/11/01'}    02:15:00    {[3.4260]}    {[0.2550]}
    {'11)'}    {'2022/11/01'}    02:30:00    {[3.2270]}    {[0.2590]}
    {'12)'}    {'2022/11/01'}    02:45:00    {[3.0390]}    {[0.2530]}
    {'13)'}    {'2022/11/01'}    03:00:00    {[2.8670]}    {[0.2420]}
    {'14)'}    {'2022/11/01'}    03:15:00    {[2.7270]}    {[0.2400]}
    {'15)'}    {'2022/11/01'}    03:30:00    {[2.6220]}    {[0.2500]}
    {'16)'}    {'2022/11/01'}    03:45:00    {[2.5350]}    {[0.2560]}

DateTime = datetime(T1.Date, 'InputFormat','yyyy/MM/dd') + timeofday(datetime(string(T1.Time)));
T1 = addvars(T1, DateTime, 'Before',2)

T1 = 2880×6 table
     Cycle           DateTime               Date           Time       ASLVBG02      Residual 
    _______    ____________________    ______________    ________    __________    __________

    {'1)' }    01-Nov-2022 00:00:00    {'2022/11/01'}    00:00:00    {[5.6160]}    {[0.2930]}
    {'2)' }    01-Nov-2022 00:15:00    {'2022/11/01'}    00:15:00    {[5.3810]}    {[0.2670]}
    {'3)' }    01-Nov-2022 00:30:00    {'2022/11/01'}    00:30:00    {[5.1300]}    {[0.2430]}
    {'4)' }    01-Nov-2022 00:45:00    {'2022/11/01'}    00:45:00    {[4.8760]}    {[0.2290]}
    {'5)' }    01-Nov-2022 01:00:00    {'2022/11/01'}    01:00:00    {[4.6100]}    {[0.2150]}
    {'6)' }    01-Nov-2022 01:15:00    {'2022/11/01'}    01:15:00    {[4.3450]}    {[0.2070]}
    {'7)' }    01-Nov-2022 01:30:00    {'2022/11/01'}    01:30:00    {[4.0930]}    {[0.2120]}
    {'8)' }    01-Nov-2022 01:45:00    {'2022/11/01'}    01:45:00    {[3.8600]}    {[0.2290]}
    {'9)' }    01-Nov-2022 02:00:00    {'2022/11/01'}    02:00:00    {[3.6370]}    {[0.2440]}
    {'10)'}    01-Nov-2022 02:15:00    {'2022/11/01'}    02:15:00    {[3.4260]}    {[0.2550]}
    {'11)'}    01-Nov-2022 02:30:00    {'2022/11/01'}    02:30:00    {[3.2270]}    {[0.2590]}
    {'12)'}    01-Nov-2022 02:45:00    {'2022/11/01'}    02:45:00    {[3.0390]}    {[0.2530]}
    {'13)'}    01-Nov-2022 03:00:00    {'2022/11/01'}    03:00:00    {[2.8670]}    {[0.2420]}
    {'14)'}    01-Nov-2022 03:15:00    {'2022/11/01'}    03:15:00    {[2.7270]}    {[0.2400]}
    {'15)'}    01-Nov-2022 03:30:00    {'2022/11/01'}    03:30:00    {[2.6220]}    {[0.2500]}
    {'16)'}    01-Nov-2022 03:45:00    {'2022/11/01'}    03:45:00    {[2.5350]}    {[0.2560]}

Check_Col_5 = T1(cellfun(@(x)~isnumeric(x),T1{:,5}),5)          % Non-Numeric Entries (Optional)

Check_Col_5 = 764×1 table
     ASLVBG02 
    __________

    {'4.170M'}
    {'3.968M'}
    {'4.174M'}
    {'3.967M'}
    {'3.681M'}
    {'3.951M'}
    {'4.221M'}
    {'4.473M'}
    {'4.729M'}
    {'4.017M'}
    {'4.205M'}
    {'3.019M'}
    {'3.245M'}
    {'3.483M'}
    {'3.733M'}
    {'3.987M'}

Check_Col_6 = T1(cellfun(@(x)~isnumeric(x),T1{:,6}),6)          % Non-Numeric Entries  (Optional)

Check_Col_6 = 764×1 table
     Residual  
    ___________

    {'0.225M' }
    {'0.233M' }
    {'-0.400M'}
    {'-0.391M'}
    {'0.571M' }
    {'0.639M' }
    {'0.696M' }
    {'0.724M' }
    {'0.750M' }
    {'0.581M' }
    {'0.590M' }
    {'0.268M' }
    {'0.261M' }
    {'0.250M' }
    {'0.236M' }
    {'0.212M' }

That should do what you want. It will likely work for other files in exactly the same format as well.

.

[kolberg]

Thank you Star!I still need the digits from those and isolate it togther with the rest without M somhow so I can use it in the plot.

[Star Strider]

As always, my pleasure!

Getting rid of the ‘M’ depends on what ‘M’ means, and if it’s importrant. The simplest way to eliminate it would be to use regexp. This involves selecting the rows with ‘M’ and elilminating the ‘M’ while leaving the other rows in each column unchanged.

C1 = readcell('https://www.mathworks.com/matlabcentral/answers/uploaded_files/1238782/IMM2211.txt')

C1 = 2891×18 cell array
    {'Port:'       }    {'P026'        }    {1×1 missing         }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'Site:'       }    {'Immingham'   }    {1×1 missing         }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'Latitude:'   }    {[     53.6310]}    {1×1 missing         }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'Longitude:'  }    {[     -0.1860]}    {1×1 missing         }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'Start'       }    {'Date:'       }    {'01NOV2022-00.00.00'}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'End'         }    {'Date:'       }    {'30NOV2022-23.45.00'}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'Contributor:'}    {'National'    }    {'Oceanography'      }    {'Centre,'  }    {'Liverpool'}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'Datum'       }    {'information:'}    {'The'               }    {'data'     }    {'refer'    }    {'to'       }    {'Admiralty'   }    {'Chart'    }    {'Datum'    }    {'(ACD)'    }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'Parameter'   }    {'code:'       }    {'ASLVBG02'          }    {'='        }    {'Surface'  }    {'elevation'}    {'(unspecified'}    {'datum)'   }    {'of'       }    {'the'      }    {'water'    }    {'body'     }    {'by'       }    {'bubbler'  }    {'tide'     }    {'gauge'    }    {'(second'  }    {'sensor)'  }
    {'Cycle'       }    {'Date'        }    {'Time'              }    {'ASLVBG02' }    {'Residual' }    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'Number'      }    {'yyyy'        }    {'mm'                }    {'dd'       }    {'hh'       }    {'mi'       }    {'ssf'         }    {'f'        }    {'f'        }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'1)'          }    {'2022/11/01'  }    {[00:00:00          ]}    {[   5.6160]}    {[   0.2930]}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'2)'          }    {'2022/11/01'  }    {[00:15:00          ]}    {[   5.3810]}    {[   0.2670]}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'3)'          }    {'2022/11/01'  }    {[00:30:00          ]}    {[   5.1300]}    {[   0.2430]}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'4)'          }    {'2022/11/01'  }    {[00:45:00          ]}    {[   4.8760]}    {[   0.2290]}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}
    {'5)'          }    {'2022/11/01'  }    {[01:00:00          ]}    {[   4.6100]}    {[   0.2150]}    {1×1 missing}    {1×1 missing   }    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}    {1×1 missing}

T1 = cell2table(C1(12:end,1:5));
T1.Properties.VariableNames = C1(10, 1:5)

T1 = 2880×5 table
     Cycle          Date           Time       ASLVBG02      Residual 
    _______    ______________    ________    __________    __________

    {'1)' }    {'2022/11/01'}    00:00:00    {[5.6160]}    {[0.2930]}
    {'2)' }    {'2022/11/01'}    00:15:00    {[5.3810]}    {[0.2670]}
    {'3)' }    {'2022/11/01'}    00:30:00    {[5.1300]}    {[0.2430]}
    {'4)' }    {'2022/11/01'}    00:45:00    {[4.8760]}    {[0.2290]}
    {'5)' }    {'2022/11/01'}    01:00:00    {[4.6100]}    {[0.2150]}
    {'6)' }    {'2022/11/01'}    01:15:00    {[4.3450]}    {[0.2070]}
    {'7)' }    {'2022/11/01'}    01:30:00    {[4.0930]}    {[0.2120]}
    {'8)' }    {'2022/11/01'}    01:45:00    {[3.8600]}    {[0.2290]}
    {'9)' }    {'2022/11/01'}    02:00:00    {[3.6370]}    {[0.2440]}
    {'10)'}    {'2022/11/01'}    02:15:00    {[3.4260]}    {[0.2550]}
    {'11)'}    {'2022/11/01'}    02:30:00    {[3.2270]}    {[0.2590]}
    {'12)'}    {'2022/11/01'}    02:45:00    {[3.0390]}    {[0.2530]}
    {'13)'}    {'2022/11/01'}    03:00:00    {[2.8670]}    {[0.2420]}
    {'14)'}    {'2022/11/01'}    03:15:00    {[2.7270]}    {[0.2400]}
    {'15)'}    {'2022/11/01'}    03:30:00    {[2.6220]}    {[0.2500]}
    {'16)'}    {'2022/11/01'}    03:45:00    {[2.5350]}    {[0.2560]}

DateTime = datetime(T1.Date, 'InputFormat','yyyy/MM/dd') + timeofday(datetime(string(T1.Time)));
T1 = addvars(T1, DateTime, 'Before',2)

T1 = 2880×6 table
     Cycle           DateTime               Date           Time       ASLVBG02      Residual 
    _______    ____________________    ______________    ________    __________    __________

    {'1)' }    01-Nov-2022 00:00:00    {'2022/11/01'}    00:00:00    {[5.6160]}    {[0.2930]}
    {'2)' }    01-Nov-2022 00:15:00    {'2022/11/01'}    00:15:00    {[5.3810]}    {[0.2670]}
    {'3)' }    01-Nov-2022 00:30:00    {'2022/11/01'}    00:30:00    {[5.1300]}    {[0.2430]}
    {'4)' }    01-Nov-2022 00:45:00    {'2022/11/01'}    00:45:00    {[4.8760]}    {[0.2290]}
    {'5)' }    01-Nov-2022 01:00:00    {'2022/11/01'}    01:00:00    {[4.6100]}    {[0.2150]}
    {'6)' }    01-Nov-2022 01:15:00    {'2022/11/01'}    01:15:00    {[4.3450]}    {[0.2070]}
    {'7)' }    01-Nov-2022 01:30:00    {'2022/11/01'}    01:30:00    {[4.0930]}    {[0.2120]}
    {'8)' }    01-Nov-2022 01:45:00    {'2022/11/01'}    01:45:00    {[3.8600]}    {[0.2290]}
    {'9)' }    01-Nov-2022 02:00:00    {'2022/11/01'}    02:00:00    {[3.6370]}    {[0.2440]}
    {'10)'}    01-Nov-2022 02:15:00    {'2022/11/01'}    02:15:00    {[3.4260]}    {[0.2550]}
    {'11)'}    01-Nov-2022 02:30:00    {'2022/11/01'}    02:30:00    {[3.2270]}    {[0.2590]}
    {'12)'}    01-Nov-2022 02:45:00    {'2022/11/01'}    02:45:00    {[3.0390]}    {[0.2530]}
    {'13)'}    01-Nov-2022 03:00:00    {'2022/11/01'}    03:00:00    {[2.8670]}    {[0.2420]}
    {'14)'}    01-Nov-2022 03:15:00    {'2022/11/01'}    03:15:00    {[2.7270]}    {[0.2400]}
    {'15)'}    01-Nov-2022 03:30:00    {'2022/11/01'}    03:30:00    {[2.6220]}    {[0.2500]}
    {'16)'}    01-Nov-2022 03:45:00    {'2022/11/01'}    03:45:00    {[2.5350]}    {[0.2560]}

NoM = @(z) cellfun(@(x)str2double(regexp(x,'(\-?)\d*\.\d*', 'match')),z);           % Eliminate 'M' Frome Selected Elements
GetNonNum = @(x) cellfun(@(x)~isnumeric(x),T1{:,x});                                % Logical Vector Of Rows With 'M'

T1{GetNonNum(5),5} = num2cell(NoM(T1{GetNonNum(5),5}));                             % Column 5 Without 'M'
T1{GetNonNum(6),6} = num2cell(NoM(T1{GetNonNum(6),6}))                              % Column 6 Without 'M'

T1 = 2880×6 table
     Cycle           DateTime               Date           Time       ASLVBG02      Residual 
    _______    ____________________    ______________    ________    __________    __________

    {'1)' }    01-Nov-2022 00:00:00    {'2022/11/01'}    00:00:00    {[5.6160]}    {[0.2930]}
    {'2)' }    01-Nov-2022 00:15:00    {'2022/11/01'}    00:15:00    {[5.3810]}    {[0.2670]}
    {'3)' }    01-Nov-2022 00:30:00    {'2022/11/01'}    00:30:00    {[5.1300]}    {[0.2430]}
    {'4)' }    01-Nov-2022 00:45:00    {'2022/11/01'}    00:45:00    {[4.8760]}    {[0.2290]}
    {'5)' }    01-Nov-2022 01:00:00    {'2022/11/01'}    01:00:00    {[4.6100]}    {[0.2150]}
    {'6)' }    01-Nov-2022 01:15:00    {'2022/11/01'}    01:15:00    {[4.3450]}    {[0.2070]}
    {'7)' }    01-Nov-2022 01:30:00    {'2022/11/01'}    01:30:00    {[4.0930]}    {[0.2120]}
    {'8)' }    01-Nov-2022 01:45:00    {'2022/11/01'}    01:45:00    {[3.8600]}    {[0.2290]}
    {'9)' }    01-Nov-2022 02:00:00    {'2022/11/01'}    02:00:00    {[3.6370]}    {[0.2440]}
    {'10)'}    01-Nov-2022 02:15:00    {'2022/11/01'}    02:15:00    {[3.4260]}    {[0.2550]}
    {'11)'}    01-Nov-2022 02:30:00    {'2022/11/01'}    02:30:00    {[3.2270]}    {[0.2590]}
    {'12)'}    01-Nov-2022 02:45:00    {'2022/11/01'}    02:45:00    {[3.0390]}    {[0.2530]}
    {'13)'}    01-Nov-2022 03:00:00    {'2022/11/01'}    03:00:00    {[2.8670]}    {[0.2420]}
    {'14)'}    01-Nov-2022 03:15:00    {'2022/11/01'}    03:15:00    {[2.7270]}    {[0.2400]}
    {'15)'}    01-Nov-2022 03:30:00    {'2022/11/01'}    03:30:00    {[2.6220]}    {[0.2500]}
    {'16)'}    01-Nov-2022 03:45:00    {'2022/11/01'}    03:45:00    {[2.5350]}    {[0.2560]}

Col_5_Num = cell2mat(T1{:,5});                                                      % Column 5 Numeric Values
Col_6_Num = cell2mat(T1{:,6});                                                      % Column 6 Numeric Values

Check_Col_5 = T1(cellfun(@(x)~isnumeric(x),T1{:,5}),5)                              % Non-Numeric Entries (Optional)

Check_Col_5 =

  0×1 empty table

Check_Col_6 = T1(cellfun(@(x)~isnumeric(x),T1{:,6}),6)                              % Non-Numeric Entries  (Optional)

Check_Col_6 =

  0×1 empty table

Eliminating the ‘M’ from the elements in their respective columns turned out to be something of an adventure! This first involved getting a logical vector of the non-numeric elements (the ‘GetNonNum’ anonymous function) and then converting only those elements to numeirc values (the ‘NoM’ or ‘ No M’ anonymous function, requiring a relatively straightforward regexp call) while ignoring the numeric elements. Even though all the elements are now numeric (the ‘Check_Col_#’ results confirm this), it’s apparently not possible to convert columns 5 and 6 to strictly numeric (rather than cell arrays of numbers) so I created ‘Col_5_Num’ and ‘Col_6_Num’ as double vectors to make them easier to use.

It might be possible to convert those columns from cell arrays to numeric arrays, however it’s not obvious to me. Nothing I’ve tried works.

.

[Stephen23]

"It might be possible to convert those columns from cell arrays to numeric arrays, however it’s not obvious to me. Nothing I’ve tried works."

Two approaches using CONVERTVARS():

C = {1;2;pi};
T0 = table(C)

T0 = 3×1 table
        C     
    __________

    {[     1]}
    {[     2]}
    {[3.1416]}

T1 = convertvars(T0,'C',@cell2mat)

T1 = 3×1 table
      C   
    ______

         1
         2
    3.1416

T2 = convertvars(T0,'C',@(a)vertcat(a{:}))

T2 = 3×1 table
      C   
    ______

         1
         2
    3.1416

Note that CONVERTVARS() can process one or more variables/columns at once.

[kolberg]

Thanks again!Where do I start to get more familiar with Matlab?

[Star Strider]

@kolberg — My recommendation would be to watch MATLAB Answers, and read the posts that you find most interesting, and relevant to your own projects.

Answer 2

[Stephen23]

This is easy and more efficient using the READTABLE() options:

fnm = 'IMM2211.txt';
obj = detectImportOptions(fnm, 'NumVariables',5,...
    'Delimiter',{' ','M',')'}, 'MultipleDelimsAsOne',true,...
    'LeadingDelimitersRule','ignore', 'TrailingDelimitersRule','ignore',...
    'VariableNamesLine',10, 'VariableUnitsLine',11);
obj = setvartype(obj,'Time','duration');
obj = setvartype(obj,'Date','datetime');
obj = setvaropts(obj,'Date','InputFormat','y/M/d');
tbl = readtable(fnm,obj)

tbl = 2880×5 table
    Cycle      Date         Time      ASLVBG02    Residual
    _____    _________    ________    ________    ________

      1      2022/11/1    00:00:00     5.616       0.293  
      2      2022/11/1    00:15:00     5.381       0.267  
      3      2022/11/1    00:30:00      5.13       0.243  
      4      2022/11/1    00:45:00     4.876       0.229  
      5      2022/11/1    01:00:00      4.61       0.215  
      6      2022/11/1    01:15:00     4.345       0.207  
      7      2022/11/1    01:30:00     4.093       0.212  
      8      2022/11/1    01:45:00      3.86       0.229  
      9      2022/11/1    02:00:00     3.637       0.244  
     10      2022/11/1    02:15:00     3.426       0.255  
     11      2022/11/1    02:30:00     3.227       0.259  
     12      2022/11/1    02:45:00     3.039       0.253  
     13      2022/11/1    03:00:00     2.867       0.242  
     14      2022/11/1    03:15:00     2.727        0.24  
     15      2022/11/1    03:30:00     2.622        0.25  
     16      2022/11/1    03:45:00     2.535       0.256  

tbl.DT = tbl.Date + tbl.Time;
tbl.DT.Format = 'yyyy/MM/dd HH:mm:ss'

tbl = 2880×6 table
    Cycle      Date         Time      ASLVBG02    Residual            DT         
    _____    _________    ________    ________    ________    ___________________

      1      2022/11/1    00:00:00     5.616       0.293      2022/11/01 00:00:00
      2      2022/11/1    00:15:00     5.381       0.267      2022/11/01 00:15:00
      3      2022/11/1    00:30:00      5.13       0.243      2022/11/01 00:30:00
      4      2022/11/1    00:45:00     4.876       0.229      2022/11/01 00:45:00
      5      2022/11/1    01:00:00      4.61       0.215      2022/11/01 01:00:00
      6      2022/11/1    01:15:00     4.345       0.207      2022/11/01 01:15:00
      7      2022/11/1    01:30:00     4.093       0.212      2022/11/01 01:30:00
      8      2022/11/1    01:45:00      3.86       0.229      2022/11/01 01:45:00
      9      2022/11/1    02:00:00     3.637       0.244      2022/11/01 02:00:00
     10      2022/11/1    02:15:00     3.426       0.255      2022/11/01 02:15:00
     11      2022/11/1    02:30:00     3.227       0.259      2022/11/01 02:30:00
     12      2022/11/1    02:45:00     3.039       0.253      2022/11/01 02:45:00
     13      2022/11/1    03:00:00     2.867       0.242      2022/11/01 03:00:00
     14      2022/11/1    03:15:00     2.727        0.24      2022/11/01 03:15:00
     15      2022/11/1    03:30:00     2.622        0.25      2022/11/01 03:30:00
     16      2022/11/1    03:45:00     2.535       0.256      2022/11/01 03:45:00

[kolberg]

Thank you Stephen,that was very handy!Merry Christmas!