This package includes functions assisting data scientists with various common tasks during the exploratory data analysis stage of a data science project. Its functions will help the data scientist to do preliminary analysis on common column types like numeric columns, categorical columns and text columns; it will also conduct several experimental clusterings on the dataset.
Our functions are tailored based on our own experience, there are also similar packages published, a few good ones worth mentioning:
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explore_numeric_columns: conducts common exploratory analysis on columns with numeric type: it generates a heatmap showing correlation coefficients (usingpearson,kendallorspearmancorrelation on choice), histograms and SPLOM plots for all numeric columns or a list of columns specified by the user. This returns a list of plot objects so that the user can save and use them later on. -
explore_categorical_columns: performs exploratory analysis on categorical features. It returns a list having a tibble with column names, corresponding unique categories, counts of null values, percentages of null values and most frequent categories along with bar plots of user provided categorical columns. -
explore_text_columns: performs exploratory data analysis of text features. If text feature columns are not specified, the function will try to identify the text features. The function prints the summary statistics of character length and word count, and plots a histogram of its distributions. It also plots the word cloud of words (after removing stopwords) and bi-grams. Bar charts of top 10 words (after removing stopwords) and top 10 bi-grams will be plotted as well. This function returns a list of all the results. -
explore_clustering: fits K-Means and DBSCAN clustering algorithms on the dataset and visualizes the clustering using scatterplots on PCA transformed data. It returns a dictionary (list) with each key being name of the clustering algorithm and the value being a list of plots generated by the models. -
explore_KMeans_clustering: fits K-Means clustering algorithms on the dataset and visualizes the clustering using scatterplots on PCA transformed data. It returns a list of plots. -
explore_DBSCAN_clustering: fits K-DBSCAN clustering algorithms on the dataset and visualizes the clustering using scatterplots on PCA transformed data. It returns a list of plots.
You can install the development version of datascience.eda with:
# install.packages("devtools")
devtools::install_github("UBC-MDS/datascience.eda.R")
library(datascience.eda)
library(palmerpenguins)
# you can call each clustering algorithm separately
explore_KMeans_clustering(penguins, centers = seq(3, 5))
#> Warning: did not converge in 10 iterations
#> Warning: did not converge in 10 iterations
#> [[1]]
#>
#> [[2]]
#>
#> [[3]]
explore_DBSCAN_clustering(penguins, eps = c(1), minPts = c(5))
#> [[1]]
# OR you can just call explore_clustering(penguins) to apply both KMeans and DBSCAN at once
library(sacred)
results <- explore_text_columns(apocrypha)
Identified the following as text columns: text
-
The average character length of text is: 131.42
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The median character length of text is: 118
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The longest text(s) has 2257 characters:
“O Lord, Almighty God of our fathers, Abraham, Isaac, and Jacob, and of their righteous seed; who hast made heaven and earth, with all the ornament thereof; who hast bound the sea by the word of thy commandment; who hast shut up the deep, and sealed it by thy terrible and glorious name; whom all men fear, and tremble before thy power; for the majesty of thy glory cannot be borne, and thine angry threatening toward sinners is importable: but thy merciful promise is unmeasurable and unsearchable; for thou art the most high Lord, of great compassion, longsuffering, very merciful, and repentest of the evils of men. Thou, O Lord, according to thy great goodness hast promised repentance and forgiveness to them that have sinned against thee: and of thine infinite mercies hast appointed repentance unto sinners, that they may be saved. Thou therefore, O Lord, that art the God of the just, hast not appointed repentance to the just, as to Abraham, and Isaac, and Jacob, which have not sinned against thee; but thou hast appointed repentance unto me that am a sinner: for I have sinned above the number of the sands of the sea. My transgressions, O Lord, are multiplied: my transgressions are multiplied, and I am not worthy to behold and see the height of heaven for the multitude of mine iniquities. I am bowed down with many iron bands, that I cannot life up mine head, neither have any release: for I have provoked thy wrath, and done evil before thee: I did not thy will, neither kept I thy commandments: I have set up abominations, and have multiplied offences. Now therefore I bow the knee of mine heart, beseeching thee of grace. I have sinned, O Lord, I have sinned, and I acknowledge mine iniquities: wherefore, I humbly beseech thee, forgive me, O Lord, forgive me, and destroy me not with mine iniquites. Be not angry with me for ever, by reserving evil for me; neither condemn me to the lower parts of the earth. For thou art the God, even the God of them that repent; and in me thou wilt shew all thy goodness: for thou wilt save me, that am unworthy, according to thy great mercy. Therefore I will praise thee for ever all the days of my life: for all the powers of the heavens do praise thee, and thine is the glory for ever and ever. Amen.”
- The shortest text(s) has 13 characters:
“And I did so.”
-
The average number of words in “text” is: 24.73
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The median number of words in “text” is: 22
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The text(s) in “text” with most words (408 words):
“O Lord, Almighty God of our fathers, Abraham, Isaac, and Jacob, and of their righteous seed; who hast made heaven and earth, with all the ornament thereof; who hast bound the sea by the word of thy commandment; who hast shut up the deep, and sealed it by thy terrible and glorious name; whom all men fear, and tremble before thy power; for the majesty of thy glory cannot be borne, and thine angry threatening toward sinners is importable: but thy merciful promise is unmeasurable and unsearchable; for thou art the most high Lord, of great compassion, longsuffering, very merciful, and repentest of the evils of men. Thou, O Lord, according to thy great goodness hast promised repentance and forgiveness to them that have sinned against thee: and of thine infinite mercies hast appointed repentance unto sinners, that they may be saved. Thou therefore, O Lord, that art the God of the just, hast not appointed repentance to the just, as to Abraham, and Isaac, and Jacob, which have not sinned against thee; but thou hast appointed repentance unto me that am a sinner: for I have sinned above the number of the sands of the sea. My transgressions, O Lord, are multiplied: my transgressions are multiplied, and I am not worthy to behold and see the height of heaven for the multitude of mine iniquities. I am bowed down with many iron bands, that I cannot life up mine head, neither have any release: for I have provoked thy wrath, and done evil before thee: I did not thy will, neither kept I thy commandments: I have set up abominations, and have multiplied offences. Now therefore I bow the knee of mine heart, beseeching thee of grace. I have sinned, O Lord, I have sinned, and I acknowledge mine iniquities: wherefore, I humbly beseech thee, forgive me, O Lord, forgive me, and destroy me not with mine iniquites. Be not angry with me for ever, by reserving evil for me; neither condemn me to the lower parts of the earth. For thou art the God, even the God of them that repent; and in me thou wilt shew all thy goodness: for thou wilt save me, that am unworthy, according to thy great mercy. Therefore I will praise thee for ever all the days of my life: for all the powers of the heavens do praise thee, and thine is the glory for ever and ever. Amen.”
End of Exploratory Data Analysis of Text Columns
results <- explore_numeric_columns(penguins)
library(dplyr)
library(MASS)
df <- data.frame(lapply(survey[, c('Sex','Clap')], as.character),
stringsAsFactors=FALSE) %>% tibble()
results <- explore_categorical_columns(df, c('Sex','Clap'))
results[[1]] %>% knitr::kable()
| column_name | unique_items | no_of_nulls | percentage_missing |
|---|---|---|---|
| Sex | Female, Male, NA | 1 | 0.422 |
| Clap | Left, Neither, Right, NA | 1 | 0.422 |
results[[2]][[1]]
results[[2]][[2]]
