pandas函数

刘超 11天前 ⋅ 769 阅读   编辑

目录
  1、pandas方法
  2、Dataframe属性方法
  3、Series属性/方法
      3.1、str属性
      3.2、tolist方法

 

  以下基于python2.7.10、pandas0.24.2测试

分类 属性/函数 描述 示例
pandas
pd.to_datetime(arg,errors, dayfirst, yearfirst, utc, box, format, exact, unit, infer_datetime_format, origin, cache, tz, convert_listlike, result, cache_array, Series, values) 字符串转时间 to_datetime使用示例
最好指定format,否者可能有些时间解析是对的,有些时间解析是错的
Dataframe 构造函数
pd.DataFrame([data, index, columns, dtype, copy]) 构造数据框 Pandas 创建DataFrame
dataframe合并
pd.concat(objs, axis=0, join='outer', join_axes=None, ignore_index=False, keys=None, levels=None, names=None, verify_integrity=False, sort=None, copy=True) 按schema合并dataframe concat函数示例
属性和数据
DataFrame.axes index: 行标签;columns: 列标签
DataFrame.as_matrix([columns]) 转换为矩阵
DataFrame.dtypes 返回数据的类型
DataFrame.ftypes 返回每一列的 数据类型float64:dense
DataFrame.get_dtype_counts() 返回数据框数据类型的个数
DataFrame.get_ftype_counts() 返回数据框数据类型float64:dense的个数
DataFrame.select_dtypes([include, include]) 根据数据类型选取子数据框
DataFrame.values Numpy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() 每一列的存储
类型转换
DataFrame.astype(dtype[, copy, errors]) 转换数据类型 astype函数示例
DataFrame.copy([deep]) deep深度复制数据
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
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,使用名称
DataFrame.iloc 整型定位,使用数字
DataFrame.insert(loc, column, value) 在特殊地点loc[数字]插入column[列名]某列数据
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, …]) 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
DataFrame.add(other[,axis,fill_value]) 加法,元素指向
DataFrame.sub(other[,axis,fill_value])         减法,元素指向
DataFrame.mul(other[, axis,fill_value])        乘法,元素指向
DataFrame.div(other[, axis,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,fill_value])        模运算,元素指向
DataFrame.pow(other[, axis,fill_value])        幂运算,元素指向
DataFrame.radd(other[, axis,fill_value])       右侧加法,元素指向
DataFrame.rsub(other[, axis,fill_value])       右侧减法,元素指向
DataFrame.rmul(other[, axis,fill_value])       右侧乘法,元素指向
DataFrame.rdiv(other[, axis,fill_value])       右侧小数除法,元素指向
DataFrame.rtruediv(other[, axis, …])           右侧真除法,元素指向
DataFrame.rfloordiv(other[, axis, …])          右侧向下取整除法,元素指向
DataFrame.rmod(other[, axis,fill_value])       右侧模运算,元素指向
DataFrame.rpow(other[, axis,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
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,  …])       指数权重窗口
描述统计学
DataFrame.abs() 返回绝对值
DataFrame.all([axis, bool_only, skipna])       Return whether all elements are True over requested axis
DataFrame.any([axis, bool_only, skipna])       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 示例
DataFrame.diff([periods, axis])                1st discrete difference of object
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
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 subset指定的字段类型需一致
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. rename函数示例
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])       Analogous to ndarray.take
DataFrame.truncate([before, after, axis ])     Truncates a sorted NDFrame before and/or after some particular index value.
处理缺失值
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’. replace示例
从新定型&排序&转变形态
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.T                                    Transpose 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
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. assign中使用format格式化会报错,可以通过round、astype变通处理一下
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
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])      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.
文件
pd.read_csv(path,[, header, skiprows, …])     读取csv read_csv函数示例
pd.read_excel(path,[, header, skiprows, …])     读取excel
作图
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
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_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.
Series
字符串操作
str属性
Series.str.split(pat=None, n=-1, expand=False) 正序分割列
Series.str.rsplit(pat=None, n=-1, expand=False) 逆序分割列
集合
tolist() Series转list

参考文章
1、https://blog.csdn.net/u011995719/article/details/72598935
2、http://liao.cpython.org/pandas13/#132


注意:本文归作者所有,未经作者允许,不得转载

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