A data analysis library comparable to pandas

You must have cython installed. Run python setup.py build_ext --use-cython -i

• A minimal set of features
• Be as explicit as possible
• There should be one-- and preferably only one --obvious way to do it.

• Only DataFrames
• No Series

All data types allow nulls

• bool - always 8 bits
• int
• float
• str - stored as a categorical
• datetime
• timedelta

• No hierarchical index
• Column names must be strings
• Column names must be unique

• No row labels for now
• Only a number display on the output

• Only one way to select data - [ ]
• Subset selection will be explicit and necessitate both rows and columns
• Rows will be selected only by integer location
• Columns will be selected by either label or integer location. Since columns must be strings, this will not be amibguous
• Slice notation is also OK

• Must use type hints
• Must use 3.6+ - fstrings
• numpy

• Easier to write idiomatically
• String processing will be much faster
• Nulls allowed in each data type
• Nearly all operations will be faster

• size
• shape
• values
• dtypes

Stats

• abs
• all
• any
• argmax
• argmin
• clip
• corr
• count
• cov
• cummax
• cummin
• cumprod
• cumsum
• describe
• max
• min
• median
• mean
• mode
• nlargest
• nsmallest
• prod
• quantile
• rank
• round
• std
• streak
• sum
• var
• unique
• nunique
• value_counts

Selection

• drop
• head
• isin
• rename
• sample
• select_dtypes
• tail
• where

Missing Data

• isna
• dropna
• fillna
• interpolate

Other

• append
• astype
• factorize
• groupby
• iterrows
• join
• melt
• pivot
• replace
• rolling
• sort_values
• to_csv

Other (after 0.1 release)

• cut
• plot
• profile

Functions

• read_csv
• read_sql
• concat

Group By - specifically with groupby method

• agg
• all
• apply
• any
• corr
• count
• cov
• cumcount
• cummax
• cummin
• cumsum
• cumprod
• head
• first
• fillna
• filter
• last
• max
• median
• min
• ngroups
• nunique
• prod
• quantile
• rank
• rolling
• size
• sum
• tail
• var

str - df.str.<method>

• capitalize
• cat
• center
• contains
• count
• endswith
• find
• findall
• get
• get_dummies
• isalnum
• isalpha
• isdecimal
• isdigit
• islower
• isnumeric
• isspace
• istitle
• isupper
• join
• len
• ljust
• lower
• lstrip
• partition
• repeat
• replace
• rfind
• rjust
• rpartition
• rsplit
• rstrip
• slice
• slice_replace
• split
• startswith
• strip
• swapcase
• title
• translate
• upper
• wrap
• zfill

dt - df.dt.<method>

• ceil
• day
• day_of_week
• day_of_year
• days_in_month
• floor
• freq
• hour
• is_leap_year
• is_month_end
• is_month_start
• is_quarter_end
• is_quarter_start
• is_year_end
• is_year_start
• microsecond
• millisecond
• minute
• month
• nanosecond
• quarter
• round
• second
• strftime
• to_pydatetime
• to_pytime
• tz
• tz_convert
• tz_localize
• weekday_name
• week_of_year
• year

td - df.td.<method>

• ceil
• components
• days
• floor
• freq
• microseconds
• milliseconds
• nanoseconds
• round
• seconds
• to_pytimedelta