pandas.DataFrame — pandas 0.16.2 documentation (original) (raw)
abs()
Return an object with absolute value taken.
add(other[, axis, level, fill_value])
Addition of dataframe and other, element-wise (binary operator add).
add_prefix(prefix)
Concatenate prefix string with panel items names.
add_suffix(suffix)
Concatenate suffix string with panel items names
align(other[, join, axis, level, copy, ...])
Align two object on their axes with the
all([axis, bool_only, skipna, level])
Return whether all elements are True over requested axis
any([axis, bool_only, skipna, level])
Return whether any element is True over requested axis
append(other[, ignore_index, verify_integrity])
Append rows of other to the end of this frame, returning a new object.
apply(func[, axis, broadcast, raw, reduce, args])
Applies function along input axis of DataFrame.
applymap(func)
Apply a function to a DataFrame that is intended to operate elementwise, i.e.
Convert the frame to a dict of dtype -> Constructor Types that each has a homogeneous dtype.
as_matrix([columns])
Convert the frame to its Numpy-array representation.
asfreq(freq[, method, how, normalize])
Convert all TimeSeries inside to specified frequency using DateOffset objects.
assign(**kwargs)
Assign new columns to a DataFrame, returning a new object (a copy) with all the original columns in addition to the new ones.
astype(dtype[, copy, raise_on_error])
Cast object to input numpy.dtype
at_time(time[, asof])
Select values at particular time of day (e.g.
between_time(start_time, end_time[, ...])
Select values between particular times of the day (e.g., 9:00-9:30 AM)
bfill([axis, inplace, limit, downcast])
Synonym for NDFrame.fillna(method=’bfill’)
bool()
Return the bool of a single element PandasObject
boxplot([column, by, ax, fontsize, rot, ...])
Make a box plot from DataFrame column optionally grouped by some columns or
clip([lower, upper, out, axis])
Trim values at input threshold(s)
clip_lower(threshold[, axis])
Return copy of the input with values below given value(s) truncated
clip_upper(threshold[, axis])
Return copy of input with values above given value(s) truncated
combine(other, func[, fill_value, overwrite])
Add two DataFrame objects and do not propagate NaN values, so if for a
combineAdd(other)
Add two DataFrame objects and do not propagate
combineMult(other)
Multiply two DataFrame objects and do not propagate NaN values, so if
combine_first(other)
Combine two DataFrame objects and default to non-null values in frame calling the method.
compound([axis, skipna, level])
Return the compound percentage of the values for the requested axis
consolidate([inplace])
Compute NDFrame with “consolidated” internals (data of each dtype grouped together in a single ndarray).
convert_objects([convert_dates, ...])
Attempt to infer better dtype for object columns
copy([deep])
Make a copy of this object
corr([method, min_periods])
Compute pairwise correlation of columns, excluding NA/null values
corrwith(other[, axis, drop])
Compute pairwise correlation between rows or columns of two DataFrame objects.
count([axis, level, numeric_only])
Return Series with number of non-NA/null observations over requested axis.
cov([min_periods])
Compute pairwise covariance of columns, excluding NA/null values
cummax([axis, dtype, out, skipna])
Return cumulative max over requested axis.
cummin([axis, dtype, out, skipna])
Return cumulative min over requested axis.
cumprod([axis, dtype, out, skipna])
Return cumulative prod over requested axis.
cumsum([axis, dtype, out, skipna])
Return cumulative sum over requested axis.
describe([percentile_width, percentiles, ...])
Generate various summary statistics, excluding NaN values.
diff([periods, axis])
1st discrete difference of object
div(other[, axis, level, fill_value])
Floating division of dataframe and other, element-wise (binary operator truediv).
divide(other[, axis, level, fill_value])
Floating division of dataframe and other, element-wise (binary operator truediv).
dot(other)
Matrix multiplication with DataFrame or Series objects
drop(labels[, axis, level, inplace, errors])
Return new object with labels in requested axis removed
drop_duplicates(*args, **kwargs)
Return DataFrame with duplicate rows removed, optionally only
dropna([axis, how, thresh, subset, inplace])
Return object with labels on given axis omitted where alternately any
duplicated(*args, **kwargs)
Return boolean Series denoting duplicate rows, optionally only
eq(other[, axis, level])
Wrapper for flexible comparison methods eq
equals(other)
Determines if two NDFrame objects contain the same elements.
eval(expr, **kwargs)
Evaluate an expression in the context of the calling DataFrame instance.
ffill([axis, inplace, limit, downcast])
Synonym for NDFrame.fillna(method=’ffill’)
fillna([value, method, axis, inplace, ...])
Fill NA/NaN values using the specified method
filter([items, like, regex, axis])
Restrict the info axis to set of items or wildcard
first(offset)
Convenience method for subsetting initial periods of time series data
Return label for first non-NA/null value
floordiv(other[, axis, level, fill_value])
Integer division of dataframe and other, element-wise (binary operator floordiv).
from_csv(path[, header, sep, index_col, ...])
Read delimited file into DataFrame
from_dict(data[, orient, dtype])
Construct DataFrame from dict of array-like or dicts
from_items(items[, columns, orient])
Convert (key, value) pairs to DataFrame.
from_records(data[, index, exclude, ...])
Convert structured or record ndarray to DataFrame
ge(other[, axis, level])
Wrapper for flexible comparison methods ge
get(key[, default])
Get item from object for given key (DataFrame column, Panel slice, etc.).
Return the counts of dtypes in this object
Return the counts of ftypes in this object
get_value(index, col[, takeable])
Quickly retrieve single value at passed column and index
same as values (but handles sparseness conversions)
groupby([by, axis, level, as_index, sort, ...])
Group series using mapper (dict or key function, apply given function
gt(other[, axis, level])
Wrapper for flexible comparison methods gt
head([n])
Returns first n rows
hist(data[, column, by, grid, xlabelsize, ...])
Draw histogram of the DataFrame’s series using matplotlib / pylab.
icol(i)
idxmax([axis, skipna])
Return index of first occurrence of maximum over requested axis.
idxmin([axis, skipna])
Return index of first occurrence of minimum over requested axis.
iget_value(i, j)
info([verbose, buf, max_cols, memory_usage, ...])
Concise summary of a DataFrame.
insert(loc, column, value[, allow_duplicates])
Insert column into DataFrame at specified location.
interpolate([method, axis, limit, inplace, ...])
Interpolate values according to different methods.
irow(i[, copy])
isin(values)
Return boolean DataFrame showing whether each element in the DataFrame is contained in values.
isnull()
Return a boolean same-sized object indicating if the values are null
Iterator over (column, series) pairs
iterkv(*args, **kwargs)
iteritems alias used to get around 2to3. Deprecated
iterrows()
Iterate over rows of DataFrame as (index, Series) pairs.
itertuples([index])
Iterate over rows of DataFrame as tuples, with index value
join(other[, on, how, lsuffix, rsuffix, sort])
Join columns with other DataFrame either on index or on a key column.
keys()
Get the ‘info axis’ (see Indexing for more)
kurt([axis, skipna, level, numeric_only])
Return unbiased kurtosis over requested axis using Fishers definition of kurtosis (kurtosis of normal == 0.0).
kurtosis([axis, skipna, level, numeric_only])
Return unbiased kurtosis over requested axis using Fishers definition of kurtosis (kurtosis of normal == 0.0).
last(offset)
Convenience method for subsetting final periods of time series data
Return label for last non-NA/null value
le(other[, axis, level])
Wrapper for flexible comparison methods le
load(path)
Deprecated.
lookup(row_labels, col_labels)
Label-based “fancy indexing” function for DataFrame.
lt(other[, axis, level])
Wrapper for flexible comparison methods lt
mad([axis, skipna, level])
Return the mean absolute deviation of the values for the requested axis
mask(cond[, other, inplace, axis, level, ...])
Return an object of same shape as self and whose corresponding entries are from self where cond is False and otherwise are from other.
max([axis, skipna, level, numeric_only])
This method returns the maximum of the values in the object.
mean([axis, skipna, level, numeric_only])
Return the mean of the values for the requested axis
median([axis, skipna, level, numeric_only])
Return the median of the values for the requested axis
memory_usage([index])
Memory usage of DataFrame columns.
merge(right[, how, on, left_on, right_on, ...])
Merge DataFrame objects by performing a database-style join operation by columns or indexes.
min([axis, skipna, level, numeric_only])
This method returns the minimum of the values in the object.
mod(other[, axis, level, fill_value])
Modulo of dataframe and other, element-wise (binary operator mod).
mode([axis, numeric_only])
Gets the mode(s) of each element along the axis selected.
mul(other[, axis, level, fill_value])
Multiplication of dataframe and other, element-wise (binary operator mul).
multiply(other[, axis, level, fill_value])
Multiplication of dataframe and other, element-wise (binary operator mul).
ne(other[, axis, level])
Wrapper for flexible comparison methods ne
notnull()
Return a boolean same-sized object indicating if the values are
pct_change([periods, fill_method, limit, freq])
Percent change over given number of periods.
pipe(func, *args, **kwargs)
Apply func(self, *args, **kwargs)
pivot([index, columns, values])
Reshape data (produce a “pivot” table) based on column values.
pivot_table(data[, values, index, columns, ...])
Create a spreadsheet-style pivot table as a DataFrame.
plot(data[, x, y, kind, ax, subplots, ...])
Make plots of DataFrame using matplotlib / pylab.
pop(item)
Return item and drop from frame.
pow(other[, axis, level, fill_value])
Exponential power of dataframe and other, element-wise (binary operator pow).
prod([axis, skipna, level, numeric_only])
Return the product of the values for the requested axis
product([axis, skipna, level, numeric_only])
Return the product of the values for the requested axis
quantile([q, axis, numeric_only])
Return values at the given quantile over requested axis, a la numpy.percentile.
query(expr, **kwargs)
Query the columns of a frame with a boolean expression.
radd(other[, axis, level, fill_value])
Addition of dataframe and other, element-wise (binary operator radd).
rank([axis, numeric_only, method, ...])
Compute numerical data ranks (1 through n) along axis.
rdiv(other[, axis, level, fill_value])
Floating division of dataframe and other, element-wise (binary operator rtruediv).
reindex([index, columns])
Conform DataFrame to new index with optional filling logic, placing NA/NaN in locations having no value in the previous index.
reindex_axis(labels[, axis, method, level, ...])
Conform input object to new index with optional filling logic, placing NA/NaN in locations having no value in the previous index.
reindex_like(other[, method, copy, limit])
return an object with matching indicies to myself
rename([index, columns])
Alter axes input function or functions.
rename_axis(mapper[, axis, copy, inplace])
Alter index and / or columns using input function or functions.
reorder_levels(order[, axis])
Rearrange index levels using input order.
replace([to_replace, value, inplace, limit, ...])
Replace values given in ‘to_replace’ with ‘value’.
resample(rule[, how, axis, fill_method, ...])
Convenience method for frequency conversion and resampling of regular time-series data.
reset_index([level, drop, inplace, ...])
For DataFrame with multi-level index, return new DataFrame with labeling information in the columns under the index names, defaulting to ‘level_0’, ‘level_1’, etc.
rfloordiv(other[, axis, level, fill_value])
Integer division of dataframe and other, element-wise (binary operator rfloordiv).
rmod(other[, axis, level, fill_value])
Modulo of dataframe and other, element-wise (binary operator rmod).
rmul(other[, axis, level, fill_value])
Multiplication of dataframe and other, element-wise (binary operator rmul).
rpow(other[, axis, level, fill_value])
Exponential power of dataframe and other, element-wise (binary operator rpow).
rsub(other[, axis, level, fill_value])
Subtraction of dataframe and other, element-wise (binary operator rsub).
rtruediv(other[, axis, level, fill_value])
Floating division of dataframe and other, element-wise (binary operator rtruediv).
sample([n, frac, replace, weights, ...])
Returns a random sample of items from an axis of object.
save(path)
Deprecated.
select(crit[, axis])
Return data corresponding to axis labels matching criteria
select_dtypes([include, exclude])
Return a subset of a DataFrame including/excluding columns based on their dtype.
sem([axis, skipna, level, ddof, numeric_only])
Return unbiased standard error of the mean over requested axis.
set_axis(axis, labels)
public verson of axis assignment
set_index(keys[, drop, append, inplace, ...])
Set the DataFrame index (row labels) using one or more existing columns.
set_value(index, col, value[, takeable])
Put single value at passed column and index
shift([periods, freq, axis])
Shift index by desired number of periods with an optional time freq
skew([axis, skipna, level, numeric_only])
Return unbiased skew over requested axis
slice_shift([periods, axis])
Equivalent to shift without copying data.
sort([columns, axis, ascending, inplace, ...])
Sort DataFrame either by labels (along either axis) or by the values in
sort_index([axis, by, ascending, inplace, ...])
Sort DataFrame either by labels (along either axis) or by the values in
sortlevel([level, axis, ascending, inplace, ...])
Sort multilevel index by chosen axis and primary level.
squeeze()
squeeze length 1 dimensions
stack([level, dropna])
Pivot a level of the (possibly hierarchical) column labels, returning a DataFrame (or Series in the case of an object with a single level of column labels) having a hierarchical index with a new inner-most level of row labels.
std([axis, skipna, level, ddof, numeric_only])
Return unbiased standard deviation over requested axis.
sub(other[, axis, level, fill_value])
Subtraction of dataframe and other, element-wise (binary operator sub).
subtract(other[, axis, level, fill_value])
Subtraction of dataframe and other, element-wise (binary operator sub).
sum([axis, skipna, level, numeric_only])
Return the sum of the values for the requested axis
swapaxes(axis1, axis2[, copy])
Interchange axes and swap values axes appropriately
swaplevel(i, j[, axis])
Swap levels i and j in a MultiIndex on a particular axis
tail([n])
Returns last n rows
take(indices[, axis, convert, is_copy])
Analogous to ndarray.take
to_clipboard([excel, sep])
Attempt to write text representation of object to the system clipboard This can be pasted into Excel, for example.
to_csv([path_or_buf, sep, na_rep, ...])
Write DataFrame to a comma-separated values (csv) file
to_dense()
Return dense representation of NDFrame (as opposed to sparse)
to_dict(*args, **kwargs)
Convert DataFrame to dictionary.
to_excel(excel_writer[, sheet_name, na_rep, ...])
Write DataFrame to a excel sheet
to_gbq(destination_table[, project_id, ...])
Write a DataFrame to a Google BigQuery table.
to_hdf(path_or_buf, key, **kwargs)
activate the HDFStore
to_html([buf, columns, col_space, colSpace, ...])
Render a DataFrame as an HTML table.
to_json([path_or_buf, orient, date_format, ...])
Convert the object to a JSON string.
to_latex([buf, columns, col_space, ...])
Render a DataFrame to a tabular environment table.
to_msgpack([path_or_buf])
msgpack (serialize) object to input file path
to_panel()
Transform long (stacked) format (DataFrame) into wide (3D, Panel) format.
to_period([freq, axis, copy])
Convert DataFrame from DatetimeIndex to PeriodIndex with desired
to_pickle(path)
Pickle (serialize) object to input file path
to_records([index, convert_datetime64])
Convert DataFrame to record array.
to_sparse([fill_value, kind])
Convert to SparseDataFrame
to_sql(name, con[, flavor, schema, ...])
Write records stored in a DataFrame to a SQL database.
to_stata(fname[, convert_dates, ...])
A class for writing Stata binary dta files from array-like objects
to_string([buf, columns, col_space, ...])
Render a DataFrame to a console-friendly tabular output.
to_timestamp([freq, how, axis, copy])
Cast to DatetimeIndex of timestamps, at beginning of period
to_wide(*args, **kwargs)
Transpose index and columns
truediv(other[, axis, level, fill_value])
Floating division of dataframe and other, element-wise (binary operator truediv).
truncate([before, after, axis, copy])
Truncates a sorted NDFrame before and/or after some particular dates.
tshift([periods, freq, axis])
Shift the time index, using the index’s frequency if available
tz_convert(tz[, axis, level, copy])
Convert tz-aware axis to target time zone.
tz_localize(*args, **kwargs)
Localize tz-naive TimeSeries to target time zone
unstack([level])
Pivot a level of the (necessarily hierarchical) index labels, returning a DataFrame having a new level of column labels whose inner-most level consists of the pivoted index labels.
update(other[, join, overwrite, ...])
Modify DataFrame in place using non-NA values from passed DataFrame.
var([axis, skipna, level, ddof, numeric_only])
Return unbiased variance over requested axis.
where(cond[, other, inplace, axis, level, ...])
Return an object of same shape as self and whose corresponding entries are from self where cond is True and otherwise are from other.
xs(key[, axis, level, copy, drop_level])
Returns a cross-section (row(s) or column(s)) from the Series/DataFrame.