Make a list of strings to frequency of words
Project description
# TTCPy - Text To Columns Python
This is the Python version of the original TTC package in R. The purpose of the package is to filter strings of non-frequent words and transform it to columns with the frequency of the common words.
The package is not big, the three things to remember, for the moment, is:
- - -
1. The initial process of the class. Give it paramters such as minimum support between a value of 0 and 1. Remember, the lower the `minSup` is, the more time it will take to compute.
```
init = TTC(data, minSup)
```
The parameters:
- `data`: Is the list of strings that you want to transform.
- `minSup`: If the frequency of the word is below this value, then it is filtered out. A value between 0 and 1.
- - -
2. Later you can call the compute function that will compute it with the given data. The output will be a `numpy` array with the frequencies of the words.
```
init.compute()
```
- - -
3. You can also call the words that is the most frequent. These words are in the same order as the output from step 2. The output will be a `numpy` array with the frequent words.
```
init.header
```
--- Updates for package TTCPy ---
- 19/07/2018 - Version 0.2.0
Introduced the `numba` module for some functions. Also took away the dependency of the module `re`.
- 11/07/2018 - Version 0.1.0
Implemented the TTC version from R to Python (TTCPy). There is not option for filtering out specific words as in the R package.
This is the Python version of the original TTC package in R. The purpose of the package is to filter strings of non-frequent words and transform it to columns with the frequency of the common words.
The package is not big, the three things to remember, for the moment, is:
- - -
1. The initial process of the class. Give it paramters such as minimum support between a value of 0 and 1. Remember, the lower the `minSup` is, the more time it will take to compute.
```
init = TTC(data, minSup)
```
The parameters:
- `data`: Is the list of strings that you want to transform.
- `minSup`: If the frequency of the word is below this value, then it is filtered out. A value between 0 and 1.
- - -
2. Later you can call the compute function that will compute it with the given data. The output will be a `numpy` array with the frequencies of the words.
```
init.compute()
```
- - -
3. You can also call the words that is the most frequent. These words are in the same order as the output from step 2. The output will be a `numpy` array with the frequent words.
```
init.header
```
--- Updates for package TTCPy ---
- 19/07/2018 - Version 0.2.0
Introduced the `numba` module for some functions. Also took away the dependency of the module `re`.
- 11/07/2018 - Version 0.1.0
Implemented the TTC version from R to Python (TTCPy). There is not option for filtering out specific words as in the R package.
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