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python--Pandas中DataFrame基本函数(略全)

python--Pandas中DataFrame基本函数(略全)

作者: 天涯海角醉云游 | 来源:发表于2018-10-25 10:57 被阅读87次

    在python中,众所周知,数据预处理最好用的包就是pandas了,以下是pandas里的dataframe数据结构常用函数。

    pandas作者Wes McKinney 在【PYTHON FOR DATA ANALYSIS】中对pandas的方方面面都有了一个权威简明的入门级的介绍。

    构造函数

    方法描述

    DataFrame([data, index, columns, dtype, copy])构造数据框

    属性和数据

    方法描述

    Axesindex: row labels;columns: column labels

    DataFrame.as_matrix([columns])转换为矩阵

    DataFrame.dtypes返回数据的类型

    DataFrame.ftypesReturn the ftypes (indication of sparse/dense and dtype) in this object.

    DataFrame.get_dtype_counts()返回数据框数据类型的个数

    DataFrame.get_ftype_counts()Return the counts of ftypes in this object.

    DataFrame.select_dtypes([include, exclude])根据数据类型选取子数据框

    DataFrame.valuesNumpy的展示方式

    DataFrame.axes返回横纵坐标的标签名

    DataFrame.ndim返回数据框的纬度

    DataFrame.size返回数据框元素的个数

    DataFrame.shape返回数据框的形状

    DataFrame.memory_usage([index, deep])Memory usage of DataFrame columns.

    类型转换

    方法描述

    DataFrame.astype(dtype[, copy, errors])转换数据类型

    DataFrame.copy([deep])复制数据框

    DataFrame.isnull()以布尔的方式返回空值

    DataFrame.notnull()以布尔的方式返回非空值

    索引和迭代

    方法描述

    DataFrame.head([n])返回前n行数据

    DataFrame.at快速标签常量访问器

    DataFrame.iat快速整型常量访问器

    DataFrame.loc标签定位

    DataFrame.iloc整型定位

    DataFrame.insert(loc, column, value[, …])在特殊地点插入行

    DataFrame.iter()Iterate over infor axis

    DataFrame.iteritems()返回列名和序列的迭代器

    DataFrame.iterrows()返回索引和序列的迭代器

    DataFrame.itertuples([index, name])Iterate over DataFrame rows as namedtuples, with index value as first element of the tuple.

    DataFrame.lookup(row_labels, col_labels)Label-based “fancy indexing” function for DataFrame.

    DataFrame.pop(item)返回删除的项目

    DataFrame.tail([n])返回最后n行

    DataFrame.xs(key[, axis, level, drop_level])Returns a cross-section (row(s) or column(s)) from the Series/DataFrame.

    DataFrame.isin(values)是否包含数据框中的元素

    DataFrame.where(cond[, other, inplace, …])条件筛选

    DataFrame.mask(cond[, other, inplace, axis, …])Return an object of same shape as self and whose corresponding entries are from self where cond is False and otherwise are from other.

    DataFrame.query(expr[, inplace])Query the columns of a frame with a boolean expression.

    二元运算

    方法描述

    DataFrame.add(other[, axis, level, fill_value])加法,元素指向

    DataFrame.sub(other[, axis, level, fill_value])减法,元素指向

    DataFrame.mul(other[, axis, level, fill_value])乘法,元素指向

    DataFrame.div(other[, axis, level, fill_value])小数除法,元素指向

    DataFrame.truediv(other[, axis, level, …])真除法,元素指向

    DataFrame.floordiv(other[, axis, level, …])向下取整除法,元素指向

    DataFrame.mod(other[, axis, level, fill_value])模运算,元素指向

    DataFrame.pow(other[, axis, level, fill_value])幂运算,元素指向

    DataFrame.radd(other[, axis, level, fill_value])右侧加法,元素指向

    DataFrame.rsub(other[, axis, level, fill_value])右侧减法,元素指向

    DataFrame.rmul(other[, axis, level, fill_value])右侧乘法,元素指向

    DataFrame.rdiv(other[, axis, level, fill_value])右侧小数除法,元素指向

    DataFrame.rtruediv(other[, axis, level, …])右侧真除法,元素指向

    DataFrame.rfloordiv(other[, axis, level, …])右侧向下取整除法,元素指向

    DataFrame.rmod(other[, axis, level, fill_value])右侧模运算,元素指向

    DataFrame.rpow(other[, axis, level, fill_value])右侧幂运算,元素指向

    DataFrame.lt(other[, axis, level])类似Array.lt

    DataFrame.gt(other[, axis, level])类似Array.gt

    DataFrame.le(other[, axis, level])类似Array.le

    DataFrame.ge(other[, axis, level])类似Array.ge

    DataFrame.ne(other[, axis, level])类似Array.ne

    DataFrame.eq(other[, axis, level])类似Array.eq

    DataFrame.combine(other, func[, fill_value, …])Add two DataFrame objects and do not propagate NaN values, so if for a

    DataFrame.combine_first(other)Combine two DataFrame objects and default to non-null values in frame calling the method.

    函数应用&分组&窗口

    方法描述

    DataFrame.apply(func[, axis, broadcast, …])应用函数

    DataFrame.applymap(func)Apply a function to a DataFrame that is intended to operate elementwise, i.e.

    DataFrame.aggregate(func[, axis])Aggregate using callable, string, dict, or list of string/callables

    DataFrame.transform(func, *args, **kwargs)Call function producing a like-indexed NDFrame

    DataFrame.groupby([by, axis, level, …])分组

    DataFrame.rolling(window[, min_periods, …])滚动窗口

    DataFrame.expanding([min_periods, freq, …])拓展窗口

    DataFrame.ewm([com, span, halflife, alpha, …])指数权重窗口

    描述统计学

    方法描述

    DataFrame.abs()返回绝对值

    DataFrame.all([axis, bool_only, skipna, level])Return whether all elements are True over requested axis

    DataFrame.any([axis, bool_only, skipna, level])Return whether any element is True over requested axis

    DataFrame.clip([lower, upper, axis])Trim values at input threshold(s).

    DataFrame.clip_lower(threshold[, axis])Return copy of the input with values below given value(s) truncated.

    DataFrame.clip_upper(threshold[, axis])Return copy of input with values above given value(s) truncated.

    DataFrame.corr([method, min_periods])返回本数据框成对列的相关性系数

    DataFrame.corrwith(other[, axis, drop])返回不同数据框的相关性

    DataFrame.count([axis, level, numeric_only])返回非空元素的个数

    DataFrame.cov([min_periods])计算协方差

    DataFrame.cummax([axis, skipna])Return cumulative max over requested axis.

    DataFrame.cummin([axis, skipna])Return cumulative minimum over requested axis.

    DataFrame.cumprod([axis, skipna])返回累积

    DataFrame.cumsum([axis, skipna])返回累和

    DataFrame.describe([percentiles, include, …])整体描述数据框

    DataFrame.diff([periods, axis])1st discrete difference of object

    DataFrame.eval(expr[, inplace])Evaluate an expression in the context of the calling DataFrame instance.

    DataFrame.kurt([axis, skipna, level, …])返回无偏峰度Fisher’s (kurtosis of normal == 0.0).

    DataFrame.mad([axis, skipna, level])返回偏差

    DataFrame.max([axis, skipna, level, …])返回最大值

    DataFrame.mean([axis, skipna, level, …])返回均值

    DataFrame.median([axis, skipna, level, …])返回中位数

    DataFrame.min([axis, skipna, level, …])返回最小值

    DataFrame.mode([axis, numeric_only])返回众数

    DataFrame.pct_change([periods, fill_method, …])返回百分比变化

    DataFrame.prod([axis, skipna, level, …])返回连乘积

    DataFrame.quantile([q, axis, numeric_only, …])返回分位数

    DataFrame.rank([axis, method, numeric_only, …])返回数字的排序

    DataFrame.round([decimals])Round a DataFrame to a variable number of decimal places.

    DataFrame.sem([axis, skipna, level, ddof, …])返回无偏标准误

    DataFrame.skew([axis, skipna, level, …])返回无偏偏度

    DataFrame.sum([axis, skipna, level, …])求和

    DataFrame.std([axis, skipna, level, ddof, …])返回标准误差

    DataFrame.var([axis, skipna, level, ddof, …])返回无偏误差

    从新索引&选取&标签操作

    方法描述

    DataFrame.add_prefix(prefix)添加前缀

    DataFrame.add_suffix(suffix)添加后缀

    DataFrame.align(other[, join, axis, level, …])Align two object on their axes with the

    DataFrame.drop(labels[, axis, level, …])返回删除的列

    DataFrame.drop_duplicates([subset, keep, …])Return DataFrame with duplicate rows removed, optionally only

    DataFrame.duplicated([subset, keep])Return boolean Series denoting duplicate rows, optionally only

    DataFrame.equals(other)两个数据框是否相同

    DataFrame.filter([items, like, regex, axis])过滤特定的子数据框

    DataFrame.first(offset)Convenience method for subsetting initial periods of time series data based on a date offset.

    DataFrame.head([n])返回前n行

    DataFrame.idxmax([axis, skipna])Return index of first occurrence of maximum over requested axis.

    DataFrame.idxmin([axis, skipna])Return index of first occurrence of minimum over requested axis.

    DataFrame.last(offset)Convenience method for subsetting final periods of time series data based on a date offset.

    DataFrame.reindex([index, columns])Conform DataFrame to new index with optional filling logic, placing NA/NaN in locations having no value in the previous index.

    DataFrame.reindex_axis(labels[, axis, …])Conform input object to new index with optional filling logic, placing NA/NaN in locations having no value in the previous index.

    DataFrame.reindex_like(other[, method, …])Return an object with matching indices to myself.

    DataFrame.rename([index, columns])Alter axes input function or functions.

    DataFrame.rename_axis(mapper[, axis, copy, …])Alter index and / or columns using input function or functions.

    DataFrame.reset_index([level, drop, …])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.

    DataFrame.sample([n, frac, replace, …])返回随机抽样

    DataFrame.select(crit[, axis])Return data corresponding to axis labels matching criteria

    DataFrame.set_index(keys[, drop, append, …])Set the DataFrame index (row labels) using one or more existing columns.

    DataFrame.tail([n])返回最后几行

    DataFrame.take(indices[, axis, convert, is_copy])Analogous to ndarray.take

    DataFrame.truncate([before, after, axis, copy])Truncates a sorted NDFrame before and/or after some particular index value.

    处理缺失值

    方法描述

    DataFrame.dropna([axis, how, thresh, …])Return object with labels on given axis omitted where alternately any

    DataFrame.fillna([value, method, axis, …])填充空值

    DataFrame.replace([to_replace, value, …])Replace values given in ‘to_replace’ with ‘value’.

    从新定型&排序&转变形态

    方法描述

    DataFrame.pivot([index, columns, values])Reshape data (produce a “pivot” table) based on column values.

    DataFrame.reorder_levels(order[, axis])Rearrange index levels using input order.

    DataFrame.sort_values(by[, axis, ascending, …])Sort by the values along either axis

    DataFrame.sort_index([axis, level, …])Sort object by labels (along an axis)

    DataFrame.nlargest(n, columns[, keep])Get the rows of a DataFrame sorted by the n largest values of columns.

    DataFrame.nsmallest(n, columns[, keep])Get the rows of a DataFrame sorted by the n smallest values of columns.

    DataFrame.swaplevel([i, j, axis])Swap levels i and j in a MultiIndex on a particular axis

    DataFrame.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.

    DataFrame.unstack([level, fill_value])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.

    DataFrame.melt([id_vars, value_vars, …])“Unpivots” a DataFrame from wide format to long format, optionally

    DataFrame.TTranspose index and columns

    DataFrame.to_panel()Transform long (stacked) format (DataFrame) into wide (3D, Panel) format.

    DataFrame.to_xarray()Return an xarray object from the pandas object.

    DataFrame.transpose(*args, **kwargs)Transpose index and columns

    Combining& joining&merging

    方法描述

    DataFrame.append(other[, ignore_index, …])追加数据

    DataFrame.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.

    DataFrame.join(other[, on, how, lsuffix, …])Join columns with other DataFrame either on index or on a key column.

    DataFrame.merge(right[, how, on, left_on, …])Merge DataFrame objects by performing a database-style join operation by columns or indexes.

    DataFrame.update(other[, join, overwrite, …])Modify DataFrame in place using non-NA values from passed DataFrame.

    时间序列

    方法描述

    DataFrame.asfreq(freq[, method, how, …])将时间序列转换为特定的频次

    DataFrame.asof(where[, subset])The last row without any NaN is taken (or the last row without

    DataFrame.shift([periods, freq, axis])Shift index by desired number of periods with an optional time freq

    DataFrame.first_valid_index()Return label for first non-NA/null value

    DataFrame.last_valid_index()Return label for last non-NA/null value

    DataFrame.resample(rule[, how, axis, …])Convenience method for frequency conversion and resampling of time series.

    DataFrame.to_period([freq, axis, copy])Convert DataFrame from DatetimeIndex to PeriodIndex with desired

    DataFrame.to_timestamp([freq, how, axis, copy])Cast to DatetimeIndex of timestamps, at beginning of period

    DataFrame.tz_convert(tz[, axis, level, copy])Convert tz-aware axis to target time zone.

    DataFrame.tz_localize(tz[, axis, level, …])Localize tz-naive TimeSeries to target time zone.

    作图

    方法描述

    DataFrame.plot([x, y, kind, ax, ….])DataFrame plotting accessor and method

    DataFrame.plot.area([x, y])面积图Area plot

    DataFrame.plot.bar([x, y])垂直条形图Vertical bar plot

    DataFrame.plot.barh([x, y])水平条形图Horizontal bar plot

    DataFrame.plot.box([by])箱图Boxplot

    DataFrame.plot.density(**kwds)核密度Kernel Density Estimate plot

    DataFrame.plot.hexbin(x, y[, C, …])Hexbin plot

    DataFrame.plot.hist([by, bins])直方图Histogram

    DataFrame.plot.kde(**kwds)核密度Kernel Density Estimate plot

    DataFrame.plot.line([x, y])线图Line plot

    DataFrame.plot.pie([y])饼图Pie chart

    DataFrame.plot.scatter(x, y[, s, c])散点图Scatter plot

    DataFrame.boxplot([column, by, ax, …])Make a box plot from DataFrame column optionally grouped by some columns or

    DataFrame.hist(data[, column, by, grid, …])Draw histogram of the DataFrame’s series using matplotlib / pylab.

    转换为其他格式

    方法描述

    DataFrame.from_csv(path[, header, sep, …])Read CSV file (DEPRECATED, please use pandas.read_csv() instead).

    DataFrame.from_dict(data[, orient, dtype])Construct DataFrame from dict of array-like or dicts

    DataFrame.from_items(items[, columns, orient])Convert (key, value) pairs to DataFrame.

    DataFrame.from_records(data[, index, …])Convert structured or record ndarray to DataFrame

    DataFrame.info([verbose, buf, max_cols, …])Concise summary of a DataFrame.

    DataFrame.to_pickle(path[, compression, …])Pickle (serialize) object to input file path.

    DataFrame.to_csv([path_or_buf, sep, na_rep, …])Write DataFrame to a comma-separated values (csv) file

    DataFrame.to_hdf(path_or_buf, key, **kwargs)Write the contained data to an HDF5 file using HDFStore.

    DataFrame.to_sql(name, con[, flavor, …])Write records stored in a DataFrame to a SQL database.

    DataFrame.to_dict([orient, into])Convert DataFrame to dictionary.

    DataFrame.to_excel(excel_writer[, …])Write DataFrame to an excel sheet

    DataFrame.to_json([path_or_buf, orient, …])Convert the object to a JSON string.

    DataFrame.to_html([buf, columns, col_space, …])Render a DataFrame as an HTML table.

    DataFrame.to_feather(fname)write out the binary feather-format for DataFrames

    DataFrame.to_latex([buf, columns, …])Render an object to a tabular environment table.

    DataFrame.to_stata(fname[, convert_dates, …])A class for writing Stata binary dta files from array-like objects

    DataFrame.to_msgpack([path_or_buf, encoding])msgpack (serialize) object to input file path

    DataFrame.to_gbq(destination_table, project_id)Write a DataFrame to a Google BigQuery table.

    DataFrame.to_records([index, convert_datetime64])Convert DataFrame to record array.

    DataFrame.to_sparse([fill_value, kind])Convert to SparseDataFrame

    DataFrame.to_dense()Return dense representation of NDFrame (as opposed to sparse)

    DataFrame.to_string([buf, columns, …])Render a DataFrame to a console-friendly tabular output.

    DataFrame.to_clipboard([excel, sep])Attempt to write text representation of object to the system clipboard This can be pasted into Excel, for example.

    参考文献: 

    http://pandas.pydata.org/pandas-docs/stable/api.html#dataframe

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