# pyerrors.input.pandas API documentation

# pyerrors.input.pandas

View Source

      1import warnings
      2import gzip
      3import sqlite3
      4import pandas as pd
      5from ..obs import Obs
      6from ..correlators import Corr
      7from .json import create_json_string, import_json_string
      8import numpy as np
      9
     10
     11def to_sql(df, table_name, db, if_exists='fail', gz=True, **kwargs):
     12    """Write DataFrame including Obs or Corr valued columns to sqlite database.
     13
     14    Parameters
     15    ----------
     16    df : pandas.DataFrame
     17        Dataframe to be written to the database.
     18    table_name : str
     19        Name of the table in the database.
     20    db : str
     21        Path to the sqlite database.
     22    if exists : str
     23        How to behave if table already exists. Options 'fail', 'replace', 'append'.
     24    gz : bool
     25        If True the json strings are gzipped.
     26
     27    Returns
     28    -------
     29    None
     30    """
     31    se_df = _serialize_df(df, gz=gz)
     32    con = sqlite3.connect(db)
     33    se_df.to_sql(table_name, con, if_exists=if_exists, index=False, **kwargs)
     34    con.close()
     35
     36
     37def read_sql(sql, db, auto_gamma=False, **kwargs):
     38    """Execute SQL query on sqlite database and obtain DataFrame including Obs or Corr valued columns.
     39
     40    Parameters
     41    ----------
     42    sql : str
     43        SQL query to be executed.
     44    db : str
     45        Path to the sqlite database.
     46    auto_gamma : bool
     47        If True applies the gamma_method to all imported Obs objects with the default parameters for
     48        the error analysis. Default False.
     49
     50    Returns
     51    -------
     52    data : pandas.DataFrame
     53        Dataframe with the content of the sqlite database.
     54    """
     55    con = sqlite3.connect(db)
     56    extract_df = pd.read_sql(sql, con, **kwargs)
     57    con.close()
     58    return _deserialize_df(extract_df, auto_gamma=auto_gamma)
     59
     60
     61def dump_df(df, fname, gz=True):
     62    """Exports a pandas DataFrame containing Obs valued columns to a (gzipped) csv file.
     63
     64    Before making use of pandas to_csv functionality Obs objects are serialized via the standardized
     65    json format of pyerrors.
     66
     67    Parameters
     68    ----------
     69    df : pandas.DataFrame
     70        Dataframe to be dumped to a file.
     71    fname : str
     72        Filename of the output file.
     73    gz : bool
     74        If True, the output is a gzipped csv file. If False, the output is a csv file.
     75
     76    Returns
     77    -------
     78    None
     79    """
     80    for column in df:
     81        serialize = _need_to_serialize(df[column])
     82        if not serialize:
     83            if all(isinstance(entry, (int, np.integer, float, np.floating)) for entry in df[column]):
     84                if any([np.isnan(entry) for entry in df[column]]):
     85                    warnings.warn("nan value in column " + column + " will be replaced by None", UserWarning)
     86
     87    out = _serialize_df(df, gz=False)
     88
     89    if not fname.endswith('.csv'):
     90        fname += '.csv'
     91
     92    if gz is True:
     93        if not fname.endswith('.gz'):
     94            fname += '.gz'
     95        out.to_csv(fname, index=False, compression='gzip')
     96    else:
     97        out.to_csv(fname, index=False)
     98
     99
    100def load_df(fname, auto_gamma=False, gz=True):
    101    """Imports a pandas DataFrame from a csv.(gz) file in which Obs objects are serialized as json strings.
    102
    103    Parameters
    104    ----------
    105    fname : str
    106        Filename of the input file.
    107    auto_gamma : bool
    108        If True applies the gamma_method to all imported Obs objects with the default parameters for
    109        the error analysis. Default False.
    110    gz : bool
    111        If True, assumes that data is gzipped. If False, assumes JSON file.
    112
    113    Returns
    114    -------
    115    data : pandas.DataFrame
    116        Dataframe with the content of the sqlite database.
    117    """
    118    if not fname.endswith('.csv') and not fname.endswith('.gz'):
    119        fname += '.csv'
    120
    121    if gz is True:
    122        if not fname.endswith('.gz'):
    123            fname += '.gz'
    124        with gzip.open(fname) as f:
    125            re_import = pd.read_csv(f, keep_default_na=False)
    126    else:
    127        if fname.endswith('.gz'):
    128            warnings.warn("Trying to read from %s without unzipping!" % fname, UserWarning)
    129        re_import = pd.read_csv(fname, keep_default_na=False)
    130
    131    return _deserialize_df(re_import, auto_gamma=auto_gamma)
    132
    133
    134def _serialize_df(df, gz=False):
    135    """Serializes all Obs or Corr valued columns into json strings according to the pyerrors json specification.
    136
    137    Parameters
    138    ----------
    139    df : pandas.DataFrame
    140        DataFrame to be serilized.
    141    gz: bool
    142        gzip the json string representation. Default False.
    143    """
    144    out = df.copy()
    145    for column in out:
    146        serialize = _need_to_serialize(out[column])
    147
    148        if serialize is True:
    149            out[column] = out[column].transform(lambda x: create_json_string(x, indent=0) if x is not None else None)
    150            if gz is True:
    151                out[column] = out[column].transform(lambda x: gzip.compress((x if x is not None else '').encode('utf-8')))
    152    return out
    153
    154
    155def _deserialize_df(df, auto_gamma=False):
    156    """Deserializes all pyerrors json strings into Obs or Corr objects according to the pyerrors json specification.
    157
    158    Parameters
    159    ----------
    160    df : pandas.DataFrame
    161        DataFrame to be deserilized.
    162    auto_gamma : bool
    163        If True applies the gamma_method to all imported Obs objects with the default parameters for
    164        the error analysis. Default False.
    165
    166    Notes:
    167    ------
    168    In case any column of the DataFrame is gzipped it is gunzipped in the process.
    169    """
    170    for column in df.select_dtypes(include="object"):
    171        if isinstance(df[column][0], bytes):
    172            if df[column][0].startswith(b"\x1f\x8b\x08\x00"):
    173                df[column] = df[column].transform(lambda x: gzip.decompress(x).decode('utf-8'))
    174        df = df.replace({r'^$': None}, regex=True)
    175        i = 0
    176        while df[column][i] is None:
    177            i += 1
    178        if isinstance(df[column][i], str):
    179            if '"program":' in df[column][i][:20]:
    180                df[column] = df[column].transform(lambda x: import_json_string(x, verbose=False) if x is not None else None)
    181                if auto_gamma is True:
    182                    if isinstance(df[column][i], list):
    183                        df[column].apply(lambda x: [o.gm() if o is not None else x for o in x])
    184                    else:
    185                        df[column].apply(lambda x: x.gm() if x is not None else x)
    186    return df
    187
    188
    189def _need_to_serialize(col):
    190    serialize = False
    191    i = 0
    192    while col[i] is None:
    193        i += 1
    194    if isinstance(col[i], (Obs, Corr)):
    195        serialize = True
    196    elif isinstance(col[i], list):
    197        if all(isinstance(o, Obs) for o in col[i]):
    198            serialize = True
    199    return serialize

def to_sql(df, table_name, db, if_exists='fail', gz=True, **kwargs): View Source

    12def to_sql(df, table_name, db, if_exists='fail', gz=True, **kwargs):
    13    """Write DataFrame including Obs or Corr valued columns to sqlite database.
    14
    15    Parameters
    16    ----------
    17    df : pandas.DataFrame
    18        Dataframe to be written to the database.
    19    table_name : str
    20        Name of the table in the database.
    21    db : str
    22        Path to the sqlite database.
    23    if exists : str
    24        How to behave if table already exists. Options 'fail', 'replace', 'append'.
    25    gz : bool
    26        If True the json strings are gzipped.
    27
    28    Returns
    29    -------
    30    None
    31    """
    32    se_df = _serialize_df(df, gz=gz)
    33    con = sqlite3.connect(db)
    34    se_df.to_sql(table_name, con, if_exists=if_exists, index=False, **kwargs)
    35    con.close()

Write DataFrame including Obs or Corr valued columns to sqlite database.

###### Parameters

- df (pandas.DataFrame): Dataframe to be written to the database.
- table_name (str): Name of the table in the database.
- db (str): Path to the sqlite database.
- if exists (str): How to behave if table already exists. Options 'fail', 'replace', 'append'.
- gz (bool): If True the json strings are gzipped.

###### Returns

- None

def read_sql(sql, db, auto_gamma=False, **kwargs): View Source

    38def read_sql(sql, db, auto_gamma=False, **kwargs):
    39    """Execute SQL query on sqlite database and obtain DataFrame including Obs or Corr valued columns.
    40
    41    Parameters
    42    ----------
    43    sql : str
    44        SQL query to be executed.
    45    db : str
    46        Path to the sqlite database.
    47    auto_gamma : bool
    48        If True applies the gamma_method to all imported Obs objects with the default parameters for
    49        the error analysis. Default False.
    50
    51    Returns
    52    -------
    53    data : pandas.DataFrame
    54        Dataframe with the content of the sqlite database.
    55    """
    56    con = sqlite3.connect(db)
    57    extract_df = pd.read_sql(sql, con, **kwargs)
    58    con.close()
    59    return _deserialize_df(extract_df, auto_gamma=auto_gamma)

Execute SQL query on sqlite database and obtain DataFrame including Obs or Corr valued columns.

###### Parameters

- sql (str): SQL query to be executed.
- db (str): Path to the sqlite database.
- auto_gamma (bool): If True applies the gamma_method to all imported Obs objects with the default parameters for the error analysis. Default False.

###### Returns

- data (pandas.DataFrame): Dataframe with the content of the sqlite database.

def dump_df(df, fname, gz=True): View Source

    62def dump_df(df, fname, gz=True):
    63    """Exports a pandas DataFrame containing Obs valued columns to a (gzipped) csv file.
    64
    65    Before making use of pandas to_csv functionality Obs objects are serialized via the standardized
    66    json format of pyerrors.
    67
    68    Parameters
    69    ----------
    70    df : pandas.DataFrame
    71        Dataframe to be dumped to a file.
    72    fname : str
    73        Filename of the output file.
    74    gz : bool
    75        If True, the output is a gzipped csv file. If False, the output is a csv file.
    76
    77    Returns
    78    -------
    79    None
    80    """
    81    for column in df:
    82        serialize = _need_to_serialize(df[column])
    83        if not serialize:
    84            if all(isinstance(entry, (int, np.integer, float, np.floating)) for entry in df[column]):
    85                if any([np.isnan(entry) for entry in df[column]]):
    86                    warnings.warn("nan value in column " + column + " will be replaced by None", UserWarning)
    87
    88    out = _serialize_df(df, gz=False)
    89
    90    if not fname.endswith('.csv'):
    91        fname += '.csv'
    92
    93    if gz is True:
    94        if not fname.endswith('.gz'):
    95            fname += '.gz'
    96        out.to_csv(fname, index=False, compression='gzip')
    97    else:
    98        out.to_csv(fname, index=False)

Exports a pandas DataFrame containing Obs valued columns to a (gzipped) csv file.

Before making use of pandas to_csv functionality Obs objects are serialized via the standardized json format of pyerrors.

###### Parameters

- df (pandas.DataFrame): Dataframe to be dumped to a file.
- fname (str): Filename of the output file.
- gz (bool): If True, the output is a gzipped csv file. If False, the output is a csv file.

###### Returns

- None

def load_df(fname, auto_gamma=False, gz=True): View Source

    101def load_df(fname, auto_gamma=False, gz=True):
    102    """Imports a pandas DataFrame from a csv.(gz) file in which Obs objects are serialized as json strings.
    103
    104    Parameters
    105    ----------
    106    fname : str
    107        Filename of the input file.
    108    auto_gamma : bool
    109        If True applies the gamma_method to all imported Obs objects with the default parameters for
    110        the error analysis. Default False.
    111    gz : bool
    112        If True, assumes that data is gzipped. If False, assumes JSON file.
    113
    114    Returns
    115    -------
    116    data : pandas.DataFrame
    117        Dataframe with the content of the sqlite database.
    118    """
    119    if not fname.endswith('.csv') and not fname.endswith('.gz'):
    120        fname += '.csv'
    121
    122    if gz is True:
    123        if not fname.endswith('.gz'):
    124            fname += '.gz'
    125        with gzip.open(fname) as f:
    126            re_import = pd.read_csv(f, keep_default_na=False)
    127    else:
    128        if fname.endswith('.gz'):
    129            warnings.warn("Trying to read from %s without unzipping!" % fname, UserWarning)
    130        re_import = pd.read_csv(fname, keep_default_na=False)
    131
    132    return _deserialize_df(re_import, auto_gamma=auto_gamma)

Imports a pandas DataFrame from a csv.(gz) file in which Obs objects are serialized as json strings.

###### Parameters

- fname (str): Filename of the input file.
- auto_gamma (bool): If True applies the gamma_method to all imported Obs objects with the default parameters for the error analysis. Default False.
- gz (bool): If True, assumes that data is gzipped. If False, assumes JSON file.

###### Returns

- data (pandas.DataFrame): Dataframe with the content of the sqlite database.