| A | B |
|---|---|
abs() | Return a Series/DataFrame with absolute numeric value of each element. |
add(other[, level, fill_value, axis]) | Return Addition of series and other, element-wise (binary operator add). |
add_prefix(prefix[, axis]) | Prefix labels with string prefix. |
add_suffix(suffix[, axis]) | Suffix labels with string suffix. |
agg([func, axis]) | Aggregate using one or more operations over the specified axis. |
aggregate([func, axis]) | Aggregate using one or more operations over the specified axis. |
align(other[, join, axis, level, copy, …]) | Align two objects on their axes with the specified join method. |
all(﹡[, axis, bool_only, skipna]) | Return whether all elements are True, potentially over an axis. |
any(﹡[, axis, bool_only, skipna]) | Return whether any element is True, potentially over an axis. |
apply(func[, args, by_row]) | Invoke function on values of Series. |
argmax([axis, skipna]) | Return int position of the largest value in the Series. |
argmin([axis, skipna]) | Return int position of the smallest value in the Series. |
argsort([axis, kind, order, stable]) | Return the integer indices that would sort the Series values. |
asfreq(freq[, method, how, normalize, …]) | Convert time series to specified frequency. |
asof(where[, subset]) | Return the last row(s) without any NaNs before where. |
astype(dtype[, copy, errors]) | Cast a pandas object to a specified dtype dtype. |
at_time(time[, asof, axis]) | Select values at particular time of day (e.g., 9:30AM). |
autocorr([lag]) | Compute the lag-N autocorrelation. |
between(left, right[, inclusive]) | Return boolean Series equivalent to left <= series <= right. |
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, limit_area]) | Fill NA/NaN values by using the next valid observation to fill the gap. |
case_when(caselist) | Replace values where the conditions are True. |
clip([lower, upper, axis, inplace]) | Trim values at input threshold(s). |
combine(other, func[, fill_value]) | Combine the Series with a Series or scalar according to func. |
combine_first(other) | Update null elements with value in the same location in ‘other’. |
compare(other[, align_axis, keep_shape, …]) | Compare to another Series and show the differences. |
convert_dtypes([infer_objects, …]) | Convert columns from numpy dtypes to the best dtypes that support pd.NA. |
copy([deep]) | Make a copy of this object’s indices and data. |
corr(other[, method, min_periods]) | Compute correlation with other Series, excluding missing values. |
count() | Return number of non-NA/null observations in the Series. |
cov(other[, min_periods, ddof]) | Compute covariance with Series, excluding missing values. |
cummax([axis, skipna]) | Return cumulative maximum over a Series. |
cummin([axis, skipna]) | Return cumulative minimum over a Series. |
cumprod([axis, skipna]) | Return cumulative product over a Series. |
cumsum([axis, skipna]) | Return cumulative sum over a Series. |
describe([percentiles, include, exclude]) | Generate descriptive statistics. |
diff([periods]) | First discrete difference of Series elements. |
div(other[, level, fill_value, axis]) | Return Floating division of series and other, element-wise (binary operator truediv). |
divide(other[, level, fill_value, axis]) | Return Floating division of series and other, element-wise (binary operator truediv). |
divmod(other[, level, fill_value, axis]) | Return Integer division and modulo of series and other, element-wise (binary operator divmod). |
dot(other) | Compute the dot product between the Series and the columns of other. |
drop([labels, axis, index, columns, level, …]) | Return Series with specified index labels removed. |
drop_duplicates(﹡[, keep, inplace, ignore_index]) | Return Series with duplicate values removed. |
droplevel(level[, axis]) | Return Series/DataFrame with requested index / column level(s) removed. |
dropna(﹡[, axis, inplace, how, ignore_index]) | Return a new Series with missing values removed. |
duplicated([keep]) | Indicate duplicate Series values. |
eq(other[, level, fill_value, axis]) | Return Equal to of series and other, element-wise (binary operator eq). |
equals(other) | Test whether two objects contain the same elements. |
ewm([com, span, halflife, alpha, …]) | Provide exponentially weighted (EW) calculations. |
expanding([min_periods, method]) | Provide expanding window calculations. |
explode([ignore_index]) | Transform each element of a list-like to a row. |
factorize([sort, use_na_sentinel]) | Encode the object as an enumerated type or categorical variable. |
ffill(﹡[, axis, inplace, limit, limit_area]) | Fill NA/NaN values by propagating the last valid observation to next valid. |
fillna(value, ﹡[, axis, inplace, limit]) | Fill NA/NaN values with value. |
filter([items, like, regex, axis]) | Subset the DataFrame or Series according to the specified index labels. |
first_valid_index() | Return index for first non-missing value or None, if no value is found. |
floordiv(other[, level, fill_value, axis]) | Return Integer division of series and other, element-wise (binary operator floordiv). |
from_arrow(data) | Construct a Series from an array-like Arrow object. |
ge(other[, level, fill_value, axis]) | Return Greater than or equal to of series and other, element-wise (binary operator ge). |
get(key[, default]) | Get item from object for given key (ex: DataFrame column). |
groupby([by, level, as_index, sort, …]) | Group Series using a mapper or by a Series of columns. |
gt(other[, level, fill_value, axis]) | Return Greater than of series and other, element-wise (binary operator gt). |
head([n]) | Return the first n rows. |
hist([by, ax, grid, xlabelsize, xrot, …]) | Draw histogram of the input series using matplotlib. |
idxmax([axis, skipna]) | Return the row label of the maximum value. |
idxmin([axis, skipna]) | Return the row label of the minimum value. |
infer_objects([copy]) | Attempt to infer better dtypes for object columns. |
info([verbose, buf, max_cols, memory_usage, …]) | Print a concise summary of a Series. |
interpolate([method, axis, limit, inplace, …]) | Fill NaN values using an interpolation method. |
isin(values) | Whether elements in Series are contained in values. |
isna() | Detect missing values. |
isnull() | Series.isnull is an alias for Series.isna. |
item() | Return the first element of the underlying data as a Python scalar. |
items() | Lazily iterate over (index, value) tuples. |
keys() | Return alias for index. |
kurt(﹡[, axis, skipna, numeric_only]) | Return unbiased kurtosis over requested axis. |
kurtosis(﹡[, axis, skipna, numeric_only]) | Return unbiased kurtosis over requested axis. |
last_valid_index() | Return index for last non-missing value or None, if no value is found. |
le(other[, level, fill_value, axis]) | Return Less than or equal to of series and other, element-wise (binary operator le). |
lt(other[, level, fill_value, axis]) | Return Greater than of series and other, element-wise (binary operator lt). |
map([func, na_action, engine]) | Map values of Series according to an input mapping or function. |
mask(cond[, other, inplace, axis, level]) | Replace values where the condition is True. |
max(﹡[, axis, skipna, numeric_only]) | Return the maximum of the values over the requested axis. |
mean(﹡[, axis, skipna, numeric_only]) | Return the mean of the values over the requested axis. |
median(﹡[, axis, skipna, numeric_only]) | Return the median of the values over the requested axis. |
memory_usage([index, deep]) | Return the memory usage of the Series. |
min(﹡[, axis, skipna, numeric_only]) | Return the minimum of the values over the requested axis. |
mod(other[, level, fill_value, axis]) | Return Modulo of series and other, element-wise (binary operator mod). |
mode([dropna]) | Return the mode(s) of the Series. |
mul(other[, level, fill_value, axis]) | Return Multiplication of series and other, element-wise (binary operator mul). |
multiply(other[, level, fill_value, axis]) | Return Multiplication of series and other, element-wise (binary operator mul). |
ne(other[, level, fill_value, axis]) | Return Not equal to of series and other, element-wise (binary operator ne). |
nlargest([n, keep]) | Return the largest n elements. |
notna() | Detect existing (non-missing) values. |
notnull() | Series.notnull is an alias for Series.notna. |
nsmallest([n, keep]) | Return the smallest n elements. |
nunique([dropna]) | Return number of unique elements in the object. |
pct_change([periods, fill_method, freq]) | Fractional change between the current and a prior element. |
pipe(func, ﹡args, ﹡﹡kwargs) | Apply chainable functions that expect Series or DataFrames. |
pop(item) | Return item and drops from series. |
pow(other[, level, fill_value, axis]) | Return Exponential power of series and other, element-wise (binary operator pow). |
prod(﹡[, axis, skipna, numeric_only, min_count]) | Return the product of the values over the requested axis. |
product(﹡[, axis, skipna, numeric_only, …]) | Return the product of the values over the requested axis. |
quantile([q, interpolation]) | Return value at the given quantile. |
radd(other[, level, fill_value, axis]) | Return Addition of series and other, element-wise (binary operator radd). |
rank([axis, method, numeric_only, …]) | Compute numerical data ranks (1 through n) along axis. |
rdiv(other[, level, fill_value, axis]) | Return Floating division of series and other, element-wise (binary operator rtruediv). |
rdivmod(other[, level, fill_value, axis]) | Return Integer division and modulo of series and other, element-wise (binary operator rdivmod). |
reindex([index, axis, method, copy, level, …]) | Conform Series to new index with optional filling logic. |
reindex_like(other[, method, copy, limit, …]) | Return an object with matching indices as other object. |
rename([index, axis, copy, inplace, level, …]) | Alter Series index labels or name. |
rename_axis([mapper, index, axis, copy, inplace]) | Set the name of the axis for the index. |
reorder_levels(order) | Rearrange index levels using input order. |
repeat(repeats[, axis]) | Repeat elements of a Series. |
replace([to_replace, value, inplace, regex]) | Replace values given in to_replace with value. |
resample(rule[, closed, label, convention, …]) | Resample time-series data. |
reset_index([level, drop, name, inplace, …]) | Generate a new DataFrame or Series with the index reset. |
rfloordiv(other[, level, fill_value, axis]) | Return Integer division of series and other, element-wise (binary operator rfloordiv). |
rmod(other[, level, fill_value, axis]) | Return Modulo of series and other, element-wise (binary operator rmod). |
rmul(other[, level, fill_value, axis]) | Return Multiplication of series and other, element-wise (binary operator rmul). |
rolling(window[, min_periods, center, …]) | Provide rolling window calculations. |
round([decimals]) | Round each value in a Series to the given number of decimals. |
rpow(other[, level, fill_value, axis]) | Return Exponential power of series and other, element-wise (binary operator rpow). |
rsub(other[, level, fill_value, axis]) | Return Subtraction of series and other, element-wise (binary operator rsub). |
rtruediv(other[, level, fill_value, axis]) | Return Floating division of series and other, element-wise (binary operator rtruediv). |
sample([n, frac, replace, weights, …]) | Return a random sample of items from an axis of object. |
searchsorted(value[, side, sorter]) | Find indices where elements should be inserted to maintain order. |
sem(﹡[, axis, skipna, ddof, numeric_only]) | Return unbiased standard error of the mean over requested axis. |
set_axis(labels, ﹡[, axis, copy]) | (DEPRECATED) Assign desired index to given axis. |
set_flags(﹡[, copy, allows_duplicate_labels]) | Return a new object with updated flags. |
shift([periods, freq, axis, fill_value, suffix]) | Shift index by desired number of periods with an optional time freq. |
skew(﹡[, axis, skipna, numeric_only]) | Return unbiased skew over requested axis. |
sort_index(﹡[, axis, level, ascending, …]) | Sort Series by index labels. |
sort_values(﹡[, axis, ascending, inplace, …]) | Sort by the values. |
squeeze([axis]) | Squeeze 1 dimensional axis objects into scalars. |
std(﹡[, axis, skipna, ddof, numeric_only]) | Return sample standard deviation. |
sub(other[, level, fill_value, axis]) | Return Subtraction of series and other, element-wise (binary operator sub). |
subtract(other[, level, fill_value, axis]) | Return Subtraction of series and other, element-wise (binary operator sub). |
sum(﹡[, axis, skipna, numeric_only, min_count]) | Return the sum of the values over the requested axis. |
swaplevel([i, j, copy]) | Swap levels i and j in a MultiIndex. |
tail([n]) | Return the last n rows. |
take(indices[, axis]) | Return the elements in the given positional indices along an axis. |
to_clipboard(﹡[, excel, sep]) | Copy object to the system clipboard. |
to_csv([path_or_buf, sep, na_rep, …]) | Write object to a comma-separated values (csv) file. |
to_dict(﹡[, into]) | Convert Series to {label -> value} dict or dict-like object. |
to_excel(excel_writer, ﹡[, sheet_name, …]) | Write object to an Excel sheet. |
to_frame([name]) | Convert Series to DataFrame. |
to_hdf(path_or_buf, ﹡, key[, mode, …]) | Write the contained data to an HDF5 file using HDFStore. |
to_json([path_or_buf, orient, date_format, …]) | Convert the object to a JSON string. |
to_latex([buf, columns, header, index, …]) | Render object to a LaTeX tabular, longtable, or nested table. |
to_list() | Return a list of the values. |
to_markdown([buf, mode, index, storage_options]) | Print Series in Markdown-friendly format. |
to_numpy([dtype, copy, na_value]) | A NumPy ndarray representing the values in this Series or Index. |
to_period([freq, copy]) | Convert Series from DatetimeIndex to PeriodIndex. |
to_pickle(path, ﹡[, compression, protocol, …]) | Pickle (serialize) object to file. |
to_sql(name, con, ﹡[, schema, if_exists, …]) | Write records stored in a DataFrame to a SQL database. |
to_string([buf, na_rep, float_format, …]) | Render a string representation of the Series. |
to_timestamp([freq, how, copy]) | Cast to DatetimeIndex of Timestamps, at beginning of period. |
to_xarray() | Return an xarray object from the pandas object. |
tolist() | Return a list of the values. |
transform(func[, axis]) | Call func on self producing a Series with the same axis shape as self. |
transpose(﹡args, ﹡﹡kwargs) | Return the transpose, which is by definition self. |
truediv(other[, level, fill_value, axis]) | Return Floating division of series and other, element-wise (binary operator truediv). |
truncate([before, after, axis, copy]) | Truncate a Series or DataFrame before and after some index value. |
tz_convert(tz[, axis, level, copy]) | Convert tz-aware axis to target time zone. |
tz_localize(tz[, axis, level, copy, …]) | Localize time zone naive index of a Series or DataFrame to target time zone. |
unique() | Return unique values of Series object. |
unstack([level, fill_value, sort]) | Unstack, also known as pivot, Series with MultiIndex to produce DataFrame. |
update(other) | Modify Series in place using values from passed Series. |
value_counts([normalize, sort, ascending, …]) | Return a Series containing counts of unique values. |
var(﹡[, axis, skipna, ddof, numeric_only]) | Return unbiased variance over requested axis. |
where(cond[, other, inplace, axis, level]) | Replace values where the condition is False. |
xs(key[, axis, level, drop_level]) | Return cross-section from the Series/DataFrame. |
(echo:: @ ᯤ)