(对时间序列很有用) pct_change 计算百分数变化 In [44]: df = DataFrame([[1.4,np.nan],[7.1,-4.5],[np.nan,np.nan],[0.75,-1.3]],index=['a','b','c','d'],columns=['one','two']) In [45]: df Out[45]: one two a 1.40 NaN b 7.10 -4.5 c NaN NaN d 0.75 -1.3 In [...
i.kind Out[532]: (6, 'medium') # change an index by passing new parameters In [533]: store.create_table_index("df", optlevel=9, kind="full") In [534]: i = store.root.df.table.cols.index.index In [535]:
当你使用链式索引时,索引操作的顺序和类型部分地确定结果是原始对象的切片,还是切片的副本。 pandas 有 SettingWithCopyWarning,因为在切片的副本上赋值通常不是有意的,而是由于链式索引返回了一个副本而预期的是一个切片引起的错误。 如果你希望 pandas 对链式索引表达式的赋值更加信任或不信任,你可以将选项 mode.chai...
You will need to do additional transforms for the type change to work correctly. Custom Conversion Functions Since this data is a little more complex to convert, we can build a custom function that we apply to each value and convert to the appropriate data type. For currency conversion (of ...
data.median(axis=0) open 21.44 high 21.97 close 10.00 low 20.98 volume 83175.93 price_change 0.05 p_change 0.26 turnover 2.50 dtype: float64 (4)idxmax()、idxmin() # 求出最大值的位置 data.idxmax(axis=0) open 2015-06-15 high 2015-06-10 close 2015-06-12 low 2015-06-12 volume 2017...
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 ...
Columns can be inserted and deleted from data structures for size mutability; Aggregating or transforming data with a powerful group by engine allowing split-apply-combine operations on data sets; High performancemergingandjoiningof data sets;
'China', 'Mongolia'])# Assigning issuethat we facedata1= data# Change a valuedata1[0]='USA'# Also changes value in old dataframedata# To prevent that, we use# creating copy of seriesnew = data.copy()# assigning new valuesnew[1]='Changed value'# printing dataprint(new)print(data)...
pct_change() Returns the percentage change between the previous and the current value pipe() Apply a function to the DataFrame pivot() Re-shape the DataFrame pivot_table() Create a spreadsheet pivot table as a DataFrame pop() Removes an element from the DataFrame pow() Raise the values of...
DataFrame:The pandas DataFrame will be in tabular format with multiple rows and columns where each column can be of different data types. Series:The Series is a one-dimensional labeled array that can store any data type, but all of its values should be of the same data type. The Series ...