memoryfm.ScrobbleLog

class memoryfm.ScrobbleLog(df, *, meta=None, update_meta=True, username=None, tz='Etc/UTC', source='manual')

Class representing a scrobble log, i.e. a sequence of scrobbles.

Parameters:

dfpd.DataFrame

A pandas DataFrame containing the scrobbles. It must have the following columns:

1. timestamp : str, int, datetime, pd.Timestamp

This column contains timestamps of scrobbles. If int, then it will be assumed to be unix epoch (milliseconds).

2. track : str

This column contains track names.

3. artist : str

This column contains artist names.

There are two optional columns:

1. album : str

This column contains album names.

2. duration : str, int, timedelta, ``pd.timedelta

This column contains durations of scrobbles/listens.

metadict, default None

A dictionary containing metadata with the following schema:

“username” (str, None) : Username for the ScrobbleLog.

“tz” (str) : Timezone IANA string

“num_scrobbles” (last.fm) or “num_listens” (str) : Number of scrobbles/listens.

“date_range” (dict) : A dictionary with keys,

1. “start” (str, None) : Date of first scrobble in isoformat

2. “end” (str, None) : Date of last scrobble in isoformat.

“source” (str, None) : Source of data (lastfmstats/spotify).

“duration_present” (bool) : True if duration column present.

“memoryfm.version” (str) : Version of memory.fm.

“schema_version” (int) : Version of metadata schema.

update_metabool, default True

If True, then meta is updated.

usernamestr, default None

username used while generating meta if no meta is passed.

tzstr, default “Etc/UTC”

tz value used while generating meta if no meta is passed.

sourcestr, default “manual”

source used while generating meta if no meta is passed.

See also

meta_generator

Generates meta from username, tz, and source

__init__(df, *, meta=None, update_meta=True, username=None, tz='Etc/UTC', source='manual')

Methods

__init__(df, *[, meta, update_meta, ...])
append(scrobbles[, drop_duplicates])	Append scrobble(s) to a ScrobbleLog.
copy()
filter_by_date([start, end, unit, include_end])	Create a ScrobbleLog filtered by date.
from_dict(data[, orient])	Create a ScrobbleLog from a canonical dict representation.
from_json([file])	Create ScrobbleLog from a canonical JSON.
from_parquet(meta_file, df_file[, start, ...])	Create a ScrobbleLog from a canonical parquet export.
from_scrobble(scrobble, meta, username, tz)	Create a ScrobbleLog from a Scrobble.
head([n])	Create a ScrobbleLog containing the first n scrobbles from the original.
tail([n])	Create a ScrobbleLog containing the last n scrobbles from the original.
to_csv([file, orient])	Write ScrobbleLog to CSV format.
to_dict([orient])	Canonical dict representation of the ScrobbleLog
to_json([file, orient, datetimefmt])	Convert a ScrobbleLog to a canonical JSON.
to_markdown([file, maxcolwidths, tablefmt, ...])	Print ScrobbleLog in a nice looking markdown format.
to_parquet(meta_file, df_file)	Write ScrobbleLog to canonical parquet.
top_charts([kind])	Get top n tracks/artists/albums by number of scrobbles.
tz_convert(tz[, inplace])	Convert ScrobbleLog timezone to another timezone.

Attributes

df	DataFrame containing scrobbles, normalised with required columns and dtypes.
meta	A dictionary containing the following metadata:
tz	The timezone for the ScrobbleLog.
username	The username for the ScrobbleLog