Series can of course just be passed into functions. However, if the function needs to be called in a chain, consider using the pipe() method. Compare the following # f, g, and h are functions taking and returning US/Eastern] In [272]: stz.dt.tz Out[272]: You can also chain these types of operations: In [273]: s.dt.tz_localize('UTC').dt.tz_convert('US/Eastern') Out[273]: useful when you dont have a reference to the DataFrame at hand. This is common when using assign in a chain of operations. For example, we can limit the DataFrame to just those observations with a Sepal Length

DataFrames and Series can be passed into functions. However, if the function needs to be called in a chain, consider using the pipe() method. First some setup: In [138]: def extract_city_name(df): .... US/Eastern] In [277]: stz.dt.tz Out[277]: You can also chain these types of operations: In [278]: s.dt.tz_localize('UTC').dt.tz_convert('US/Eastern') Out[278]: useful when you don’t have a reference to the DataFrame at hand. This is common when using assign in a chain of operations. For example, we can limit the DataFrame to just those observations with a Sepal Length

the string defined by the first argument and searches for the first position of the substring you supply as the second argument. data _null_; set tips; put(FINDW(sex,'ale')); run; Python determines the the string defined by the first argument and searches for the first position of the substring you supply as the second argument. generate str_position = strpos(sex, "ale") Python determines the position useful when you don’t have a reference to the DataFrame at hand. This is common when using assign in a chain of operations. For example, we can limit the DataFrame to just those observations with a Sepal Length

the string defined by the first argument and searches for the first position of the substring you supply as the second argument. data _null_; set tips; put(FINDW(sex,'ale')); run; Python determines the the string defined by the first argument and searches for the first position of the substring you supply as the second argument. generate str_position = strpos(sex, "ale") Python determines the position useful when you don’t have a reference to the DataFrame at hand. This is common when using assign in a chain of operations. For example, we can limit the DataFrame to just those observations with a Sepal Length

df[lambda x: 'A'] Out[19]: 0 1 1 2 2 3 Name: A, dtype: int64 Using these methods / indexers, you can chain data selection operations without using temporary variable. 1.9. v0.18.1 (May 3, 2016) 125 pandas: 28]: 'a b ? c' In [2]: pd.Series(['a','b',np.nan,'c']).str.cat(' ') ValueError: Did you mean to supply a `sep` keyword? 1.10.1.7 Datetimelike rounding DatetimeIndex, Timestamp, TimedeltaIndex, Timedelta new method DataFrame.pipe(). As suggested by the name, pipe should be used to pipe data through a chain of function calls. The goal is to avoid confusing nested function calls like 1.13. v0.16.2 (June

Series can of course just be passed into functions. However, if the function needs to be called in a chain, consider using the pipe() method. Compare the following # f, g, and h are functions taking and returning \\\\\\\\\\\\\\\\\\\\\Out[272]: ˓→ You can also chain these types of operations: In [273]: s.dt.tz_localize('UTC').dt.tz_convert('US/Eastern') Out[273]: useful when you don’t have a reference to the DataFrame at hand. This is common when using assign in a chain of operations. For example, we can limit the DataFrame to just those observations with a Sepal Length

Series can of course just be passed into functions. However, if the function needs to be called in a chain, consider using the pipe() method. Compare the following # f, g, and h are functions taking and returning \\\\\\\\\\\\\\\\\\\\\Out[272]: ˓→ You can also chain these types of operations: In [273]: s.dt.tz_localize('UTC').dt.tz_convert('US/Eastern') Out[273]: useful when you don’t have a reference to the DataFrame at hand. This is common when using assign in a chain of operations. For example, we can limit the DataFrame to just those observations with a Sepal Length

the string defined by the first argument and searches for the first position of the substring you supply as the second argument. data _null_; set tips; put(FINDW(sex,'ale')); run; You can find the position the string defined by the first argument and searches for the first position of the substring you supply as the second argument. generate str_position = strpos(sex, "ale") You can find the position of useful when you don’t have a reference to the DataFrame at hand. This is common when using assign in a chain of operations. For example, we can limit the DataFrame to just those observations with a Sepal Length

the string defined by the first argument and searches for the first position of the substring you supply as the second argument. data _null_; set tips; put(FINDW(sex,'ale')); run; You can find the position the string defined by the first argument and searches for the first position of the substring you supply as the second argument. generate str_position = strpos(sex, "ale") You can find the position of useful when you don’t have a reference to the DataFrame at hand. This is common when using assign in a chain of operations. For example, we can limit the DataFrame to just those observations with a Sepal Length

the string defined by the first argument and searches for the first position of the substring you supply as the second argument. data _null_; set tips; put(FINDW(sex,'ale')); run; You can find the position the string defined by the first argument and searches for the first position of the substring you supply as the second argument. generate str_position = strpos(sex, "ale") You can find the position of useful when you don’t have a reference to the DataFrame at hand. This is common when using assign in a chain of operations. For example, we can limit the DataFrame to just those observations with a Sepal Length